Louis Billera

EducationPh.D. (1968) City University of New York

Research Area: Geometric and algebraic combinatorics

For some time, my research has centered on combina-torial properties of convex polytopes and, more gener-ally, to algebraic approaches to combinatorial problems arising in geometry. Some questions are related to the facial structure of polytopes, for example, the enumer-ation of faces by dimension. Others have to do with subdivisions of polytopes.

A common theme in much of this has been the con-struction of polytopes to given specifications: for example the construction with Carl Lee of polytopes satisfying the conditions of McMullen’s g-conjecture, showing these conditions to be sufficient to describe the enumeration of faces of all simplicial convex poly-topes, or the construction with Bernd Sturmfels of fiber polytopes, showing that certain sets of polyhedral sub-divisions of polytopes themselves have the structure of convex polytopes. In addition, we have used some of these ideas in the study of questions arising in biology concerning the structure of the space of all phylogenetic trees.

More recently, I have been studying algebraic structures underlying the enumeration of faces and flags in polytopes and posets. This has led to the study of connections with the theory quasisymmetric and sym-metric functions and has had application to enumeration in matroids and hyperplane arrangements and to a represention of the Kazhdan-Lusztig polynomials of Bruhat intervals in a Coxeter group.

Selected Publications• Generalized Dehn-Sommerville relations for polytopes, spheres, and Eulerian partially ordered sets (with M. M. Bayer), Inv. Math. 79 (1985), 143–157.• Homology of smooth splines: generic triangulations and a conjecture of Strang, Trans. Amer. Math. Soc. 310 (1988), 325–340.• Fiber polytopes (with B. Sturmfels), Annals of Math. 135 (1992), 527–549.• Geometry of the space of phylogenetic trees (with S. Holmes and K. Vogtmann), Advances in Applied Mathematics 27 (2001), 733–767.• Peak quasisymmetric functions and Eulerian enumeration (with S. K. Hsiao and S. van Willigenburg), Advances in Mathematics 176 (2003), 248–276.• Quasisymmetric functions and Kazhdan-Lusztig polynomials (with F. Brenti), Israel Jour. Math. 184 (2011), 317–348.

Department: MathematicsTitle: ProfessorAddress: 501 Malott Hall Phone: 607-255-7149email: billera@math.cornell.edu Website: www.math.cornell.edu/~billera/

Robert Gary Bland

Selected Publications• Bland, Robert Gary, J. Cheriyan, D. Jensen, L Ladanyi. 1993. "An empirical study of network flow algorithms." In Network flows and matching: First dimacs implementation challenge, edited by D.S. Johnson and C.C. McGeogh, 119-156. . • Bland, Robert Gary, D F Shallcross. 1989, "Large traveling salesman problems arising from experiments in x-ray crystallography." Operations Research Letters 8(125-28). • Bland, Robert Gary. 1977"New finite pivoting rules for the simplex method." Mathematics of Operations Research 2(103-07). • Bland, Robert Gary, James B Orlin. 2010. "Flows in Networks". Landmarks in Mathematics and Physics Series. 208. Princeton, New Jersey: Princeton University Press. • Bland, Robert Gary, James B Orlin. 2009. "Profiles In Operations Research, eds. S. Gass and A. Assad, Springer."

Selected Awards and Honors• Outstanding Educator Award (for having most influenced Merrill Presidential Scholar Adam Schneider). (Cornell University) 2009

Department: Operations Research and Information EngineeringTitle: ProfessorAddress: 233 Frank H T Rhodes HallPhone: 607-255-9144email: rgb6@cornell.eduWebsite: people.orie.cornell.edu/bland/

James Booth

Profile I am currently Chair of the Department of Biological Statistics and Computational Biology in the College of Agriculture and Life Sciences at Cornell University. I came to Cornell in 2003 as a visitor to the Department of Operations Research and Information Engineering, and was hired in BSCB the following year. From 1987 to 2003 I was a faculty member in the Department of Statistics at the University of Florida. My main re-search interests involve basic statistical methodology including: the bootstrap and Monte Carlo methods, clustering, exact inference, mixed models, generalized linear models, applications of the saddlepoint and Laplace approximations and model fitting algoritms. Since coming to Cornell I have taught the Statistical Methods II course for graduate students from a wide variety of disciplines, Theory of Linear and General-ized Linear Models primarily for Ph.D. students in the Department of Statistical Sciences, and special topics courses on Categorical Data Analysis and Likelihood and Bayesian Statistical Methods. As a faculty member in BSCB I am also actively involved in the Cornell Sta-tistical Consulting Unit which provides free advice on statistical issues to faculty and students at Cornell.

Selected Publications• Caitlin Cunningham and James G. Booth. A bayesian approach to analysis of covariance in balanced randomized block experiments. Journal of Statistical Computation and Simulation, 2011. To appear.• Haim Bar, James Booth, Elizabeth Schifano, and Martin T. Wells. Laplace approximated em microarray analysis: an empirical bayes approach for comparative microarray experiments. Statistical Science, 25(3):388{407, 2010.• James G. Booth, Walter T. Federer, Martin T. Wells, and Russell Wol_nger. A multivariate variance component model for analysis of covariance in designed experiments. Statistical Science, 24(2):223{237, 2009.• Vadim Zipunnikov, James G. Booth, and Ruriko Yoshida. Table counting using the saddlepoint approximation. Journal of Computational and Graphical Statistics, 18(4):915{929, 2009.• James G Booth, George Casella, and James P Hobert. Clustering using objective functions and stochastic search. Journal of the Royal Statistical Society, B 70(1):119{139, 2008.

Selected Awards and Honors• ASA Fellow: 2004• Best Contributed Presentation: Joint Statistical Meetings, New York, 2003• Teaching Improvement Program Award: University of Florida, 1995• R.L. Anderson Outstanding Graduate Student: University of Kentucky, 1985

Department: Biological Statistics and Computational BiologyTitle: ProfessorAddress: 1178 Comstock HallPhone: 607-254-6505email: jb383@cornell.eduWebsite: www.bscb.cornell.edu/~booth/

Jim Dai

EducationB.S. (Mathematics), Nanjing University, 1982 M.S. (Mathematics), Nanjing University, 1985 Ph.D. (Mathematics), Stanford University, 1990

Profile Jim Dai is a professor in the School of Operations Re-search and Information Engineering (ORIE) of Cornell University. He is currently on leave from his Edenfield Professor of Industrial & Systems Engineering at Geor-gia Institute of Technology, where he has been a faculty member for 22 years. He is a Special Term Professor at Tsinghua University and a Visiting Professor in Deci-sion Sciences at National University of Singapore. For more than twenty years, he has worked on stochastic models arising from communications, manufactur-ing, and service systems that include data switches, semiconductor wafer fabrication lines, call centers, and healthcare-delivery systems.

Jim Dai received B.A. and M.S. degrees from Nanjing University and a Ph.D. degree from Stanford Uni-versity, all in mathematics. He is an elected fellow of Institute of Mathematical Statistics and an elected fellow of Institute for Operations Research and the Management Sciences (INFORMS). His awards for research contributions include the Best Publication Award in 1997 and The Erlang Prize in 1998, both from the Applied Probability Society of INFORMS. He delivered the Markov Lecture at INFORMS national meeting in October 2012. He is currently an Area Editor and the Interim Editor-in-Chief for Mathematics of Operations Research, a past Area Editor for Operations Research, and a past Series Editor for Handbooks in Operations Research and Management Science. He was recently appointed by INFORMS to be the next Editor-in-Chief for Mathematics of Operations Research effective January 1, 2013.

Selected Publications• J.G. Dai, Shuangchi He. 2010. “Customer abandonment in many-server queues.” Mathematics of Operations Research 35 (2): 347-362. • Tezcan, Tolga, J.G. Dai. 2010. “Dynamic control of N-systems with many servers: Asymptotic optimality of a static priority policy in heavy traffic.” Operations Research 58 (1): 94-110. • J.G. Dai, J H Vande Vate. 2000. “The Stability of Two-Station Multitype Fluid Networks.” Operations Research 48 (5): 721-744. • J.G. Dai, G Weiss. 1996. “Stability and instability of fluid models for re-entrant lines.” Mathematics of Operations Research 21 (1): 115-134. • J.G. Dai, J M Harrison. 1992. “Reflected Brownian motion in an orthant: numerical methods for steady-state analysis.” Annals of Applied Probability 2: 65-86.

Department: Operations Research and Information EngineeringTitle: ProfessorAddress: 226 Frank H T Rhodes HallPhone: 607-255-4223email: jd694@cornell.eduWebsite: www.orie.cornell.edu/people/profile.cfm?netid=jd694

Continued next page

Selected Awards and Honors• NSF Young Investigator Award (National Science Foundation) 1994 • The Best Publication Award (Applied Probability Society of INFORMS) 1997 • The Erlang Prize (Applied Probability Society of INFORMS) 1998 • IBM Faculty Award (IBM) 2003 • Markov Lecture at INFORMS Phoenix Meeting (Applied Probability Society of INFORMS) 2012

Eugene B. Dynkin

EducationPh.D. (1948), Dr. of Science (1951) Moscow University

Research Area: Probability theory, Lie groupsLie groups were the main subject of my earlier re-search. Dynkin's Diagrams are widely used by mathe-maticians and physicists. After 1954, probability theory became the central field of my interests. Principal ef-forts were devoted to Markov processes and their con-nections with potential theory and partial differential equations. Other work includes research in mathemati-cal statistics (sufficient statistics, exponential families), optimal control (optimal stopping, control with incom-plete data) and mathematical economics (economic growth and economic equilibrium under uncertainty).

In the 80s I worked on the relationship between Mark-ov processes and random fields that arise in statistical physics and quantum field theory. One of the results — an isomorphism theorem connecting Gaussian fields with local times for Markov processes — has a consid-erable impact on the work of a number of investiga-tors. For the last decade, my main efforts are devoted to the theory of measure-valued branching processes. (The name superprocesses suggested by me for these processes is now standard in mathematical literature.) Connections between superdiffusions and a class of nonlinear partial differential equations were established that makes it possible to apply powerful analytic tools for investigating the path behavior of superdiffusions, and that provides a new probabilistic approach to problems of nonlinear PDEs. New directions - the descrip-tion of all positive solutions of a certain class of nonlinear equations and the study of removable boundary singularities of such solutions — have been started in a series of joint papers of Dynkin and Kuznetsov. A theory developed by them and by a number of other investigators is presented in a systematic way in a monograph of Dynkin published in 2002.

Selected Publications• An Introduction to Branching Measure-Valued Processes, CRM Monograph Series 6, American Mathematical Society, Providence, RI, 1994.• Fine topology and fine trace on the boundary associated with a class of semilinear differential equations (with S. E. Kuznetsov), Comm. Pure and Appl. Math. 51 (1998), 897–936.• Selected Papers of E. B. Dynkin with Commentary, Amer. Math. Soc. and International Press, 2000.• Diffusions, Superdiffusions and Partial Differential Equations, AMS Colloquium Publications, Vol. 50, Providence, Rhode Island, 2002.• Superdiffusions and positive solutions of nonlinear partial differential equations, American Mathematical Society, University Lecture Series, Volume 34, 2004.

Department: MathematicsTitle: A. R. Bullis Professor Emeritus of MathematicsAddress: 310 Malott HallPhone: 607-255-3404email: ebd1@cornell.eduWebsite: www.math.cornell.edu/~ebd

Peter Frazier

BiographyPeter Frazier received a B.S. in Physics and Engineer-ing/Applied Science from the California Institute of Technology in 2000, after which he spent several years in industry as a software engineer. In 2005, he entered graduate school in the Department of Opera-tions Research & Information Engineering at Princeton University, and received an M.A. in 2007 and a Ph.D. in 2009. He joined the faculty at Cornell in 2009 as an As-sistant Professor in the School of Operations Research & Financial Engineering. His research is in sequential decision-making under uncertainty and optimal meth-ods for collecting information, focusing on applications in simulation, global optimization, and health-care. He is the recipient of a Young Investigator Award from the Air Force Office of Scientific Research.

Research InterestsProfessor Frazier works in sequential decision-making under uncertainty and sequential experimental design. He focuses on applications in simulation and global optimization, where the goal is to use statistical meth-ods and dynamic programming to make better deci-sions about which simulations we perform, in order to solve a simulation optimization problem more efficiently. He has also worked more broadly in other applica-tions including healthcare, logistics, inventory control, finance, computer vision, and information retrieval. In addition to work on these applied areas, he also conducts theoretical research in methods for dynamic programming and machine learning.

Teaching InterestsProfessor Frazier has taught courses in simulation and statistics, including ORIE 5582 (Monte Carlo Methods for Financial Engineering) and ORIE 6580 (Simulation), ORIE 6750 (Optimal Learning), and he will be teach-ing ORIE 3120 (Industrial Data and Systems Analysis, co-teaching with Peter Jackson) in the second half of the spring 2011 semester. In the fall, Professor Frazier will teach ORIE 3800 (Information Systems and Analy-sis). ORIE 5582 has become quite popular, both with the financial engineering MEng students required to take it, and with a number of other Masters, PhD, and undergraduate students who take the course. In previ-ous versions of the course, students used Matlab, but Prof. Frazier has modified the course so that students do homework assignments and recitations in C++. Although more difficult for students, this preparation in C++ better prepares them for the job market on Wall Street. Professor Frazier also developed a new course based on his research, ORIE 6750 (Optimal Learning), on Bayesian statistics and dynamic programming methods for collecting information optimally. Both this and the other PhD course taught by Professor Frazier were well-attended and well-liked by students.

Department: Operations Research and Information EngineeringTitle: Assistant ProfessorAddress: 232 Frank H T Rhodes HallPhone: 607-254-5243email: pf98@cornell.eduWebsite: people.orie.cornell.edu/pfrazier/

Continued next page

Service InterestsProfessor Frazier is active within INFORMS and the INFORMS Simulation Society, and is on the program committee for the 2011 INFORMS Simulation Society Research Workshop Montreal. He is also an editor for a special issue of IIE Transactions on simulation optimization, and was on the program committee for the Sec-ond International Workshop on Computational Stochastics. He organized sessions at the INFORMS annual meeting in 2010 and 2011, and at the INFORMS Healthcare conference in 2011. He also participates exten-sively as a reviewer within the operations research, machine learning, and statistics communities, and was recently nominated as an outstanding reviewer by the editors of IEEE Transactions on Automatic Control.

Selected Publications• Frazier, Peter, W B Powell. 2011"Consistency of Sequential Bayesian Sampling Policies." SIAM Journal on Control and Optimization. • Frazier, Peter, W B Powell. 2010"Paradoxes in Learning and the Marginal Value of Information." Decision Analysis (7): 327-330. • Frazier, Peter, W B. Powell, S Dayanik. 2009"The Knowledge-Gradient Policy for Correlated Normal Rewards." INFORMS Journal on Computing 21: 599-613. • Frazier, Peter, A J Yu. 2007. "Sequential Hypothesis Testing under Stochastic Deadlines". Neural Informaiton Processing Systems Conference. • Blei, D., Peter Frazier. 2011. "Distance Dependent Chinese Restaraunt Processes." Paper presented at International Conference on machine Learning research

Selected Awards and Honors• Young Investigators Research Program Award (Air Force Office of Scientific Research) 2011 • Honorable Mention (INFORMS Computing Society Student Paper Competition) 2009 • Finalist (INFORMS Doing Good with Good OR, Student Competition) 2009 • Finalist (INFORMS Decision Analysis Society Student Paper Competition) 2007 • Spotlight Paper Presentation (Neural Information Processing Systems) 2007

Nagesh Gavirneni

BiographyProfessor Gavirneni's research interests are in the areas of supply chain management, inventory control, production scheduling, simulation, and optimization. His papers have appeared in Management Science, Manufacturing & Service Operations Management, European Journal of Operational Research, Opera-tions Research Letters, IIE Transactions, Interfaces, and IEEE Transactions on Reliability. Previously, he was an assistant professor in the Kelley School of Busi-ness at Indiana University. Before that he was the chief algorithm design engineer of SmartOps, a Software Architect at Maxager Technology, Inc., and a research scientist with Schlumberger. His undergraduate degree from IIT-Madras is in Mechanical Engineering and he has received Masters Degrees from Iowa State Univer-sity and Carnegie Mellon University.

Selected Publications• Mehrotra, Mili; Dawande, Milind; Gavirneni, Srinagesh; Demirci, Mehmet; Tayur, Sridhar. "Production Planning with Patterns: A Problem from Processed Food Manufacturing" Operations Research 59.2 (2011): 267-282.• Dawande, Milind; Gavirneni, Srinagesh; Mu, Yinping; Sethi, Suresh; Sriskandarajah, Chelliah. "On the Interaction Between Demand Substitution and Production Changeovers" Manufacturing & Service Operations Management 12.4 (2010): 682-692 .• Chen, Lucy Gongtao; Gavirneni, Srinagesh. "Using Scheduled Ordering to Improve the Performance of Distribution Supply Chains" Management Science 56.9 (2010): 1615-1632.• Gavirneni, Srinagesh; Isen, Alice M.. "Anatomy of a Newsvendor or Decision: Observations from a Verbal Protocol Analysis" Production and Operations Management 19.4 (2010): 453-462.• Zhu, Wanshan; Gavirneni, Srinagesh; Kapuscinski, Roman. "Periodic Flexibility, Information Flows, and Supply Chain Performance" IIE Transactions 42.3 (2010): 173-187.

Selected Awards and Honors• 2009 Meritorious Service Award from Management Science.• Grant ($7,150) from the Jeffrey S. Lehman Fund for Scholarly Exchange with China.• Small project grant from The Institute for the Social Sciences at Cornell University.• Clifford H. Whitcomb Faculty Fellowship for the year 2007-2008.• Meritorious Service Award from Operations Research – 2002 and 2004.

Department: Operations Management, JGSMTitle: Associate ProfessorAddress: 325 Sage HallPhone: 607-254-6776email: nagesh@cornell.eduWebsite: courses.cit.cornell.edu/sg337/

Shane G. Henderson

BiographyShane G. Henderson is a professor in the School of Operations Research and Information Engineering at Cornell University.

Research InterestsShane Henderson works on the theory and applica-tion of stochastic simulation and applied probability, with emphasis on the interface between these areas and optimization. His primary research interests lie in discrete-event simulation. An emphasis in his work is the interplay between optimization and simulation. In particular, he is interested in structured simulation optimization, where the optimization problem enjoys certain properties, like convexity, that one can exploit to develop algorithms that are robust and fast. Specific applications include radiation treatment planning; call center planning, yacht match racing, ambulance de-ployment, and adaptive Monte Carlo. He is a member of the Cornell Fields of Operations Research, Applied Mathematics, Systems Engineering, and Computation-al Science and Engineering.

Teaching InterestsShane Henderson teaches courses in probability and statistics, simulation, and mathematical modeling. He is a great believer in case-based learning and uses a problem-driven classroom approach in his mathematical-modeling courses. He strives for both mathematical rigor and practical relevance in the classroom.

Service InterestsShane Henderson currently serves as the Chair of the INFORMS Applied Probability Society, he is the area editor of Operations Research, and an associate editor for both Management Science and Stochastic Sys-tems. He co-chaired the 2009 INFORMS Applied Probability Society conference, co-edited the Proceedings of the 2007 Winter Simulation Conference, co-edited the Handbook on Simulation (Elsevier), and has helped organize numerous conferences and workshops, including serving as co-chair for the INFORMS Simulation Society Research Workshop (2007, 2011) and serving on the organizing committee of the INFORMS Practice conference from 2005-2007. He is a frequently requested public speaker.

Department: Operations Research and Information EngineeringTitle: ProfessorAddress: 230 Frank H T Rhodes HallPhone: 607-255-9126email: sgh9@cornell.eduWebsite: people.orie.cornell.edu/shane/

Continued next page

Selected Publications• Maxwell, Matthew, Mateo Restrepo, Shane G. Henderson, Huseyin Topaloglu. 2010"Approximate dynamic programming for ambulance redeployment." INFORMS Journal on Computing 22: 266-281. • Henderson, Shane G. 2009. "Operations research tools for addressing current challenges in emergency medical services". • Friedman, Eric J., Shane G. Henderson, T. Byuen, G Gutierrez Gallardo. 2009"Estimating the Probability that the game of Monopoly never ends." Proceedings of the 2009 Winter Simulation Conference. • Kim, S., Shane G. Henderson. 2007"Adaptive control variates for finite-horizon simulation." Mathematics of Operations Research 32(3): 508-527. • Steckley, S. G., Shane G. Henderson. 2007"The error in steady-state approximations for the time-dependent waiting time distribution." Stochastic Models 23(2): 307-332.

Selected Awards and Honors• Professor of the Year, ORIE Master of Engineering Class (Cornell University) 2009 • Michael Tien Excellence in Teaching Award (Cornell University) 2008 • Ph.D. Colloquium Plenary Speaker (Winter Simulation Conference) 2008 • Sonny Yau '72 Excellence in Teaching Award (Cornell University) 2003 • NSF Career Award (NSF) 1999

Giles Hooker

Research Interests• Data analysis for dynamical systems and differential equations • Functional data analysis • Machine learning and data mining • Disparity-based inference

My research focuses on a number of issues within these three fields. I am particularly interested in devel-oping and extending the methods of functional data analysis for examining the evolution of systems in terms of nonlinear differential equations. This involves estimating parameters for such equations, diagnos-ing when and why equations do not fit data well and developing statistical theory to account for smooth per-turbations of such systems.

In machine learning, I focus on the problem of diag-nostics and understanding the prediction functions that machine learning produces. Recent work in this includes estimates for conditional density and quan-tile functions. I am also interested in analyzing the results of experiments in machine learning in terms of determining when and why particular methods were successful.

Lastly, I am interested in robust inference via disparity-based methods such as Hellinger distance. These techniques have been in existence for 30 years or more for iid data; part of my research focusses on adapting these to regression, mixed-effects and Bayesian frameworks.

Selected Publications• Giles Hooker and Anand Vidyashankar, 2011, "Consistency and Efficiency of Conditional Disparity Methods", Technical Report BU-1670-M, Department of Biological Statistics and Computational Biology, Cornell University. • Maria Asencio, Giles Hooker and H. Oliver Gao, 2011, "Functional Convolution Models", submitted. • Chong Liu, Surajit Ray, Giles Hooker and Mark Friedl, 2011, "Functional Factor Analysis for Periodic Remote Sensing Data", submitted. • Giles Hooker and Anand Vidyashankar, 2010, "Bayesian Model Robustness via Disparities", submitted. An online appendix detailing simulation results is also available as is a .tar file of R code to reproduce all our results. • Darrell Sonntag, H. Oliver Gao and Giles Hooker, 2010, "Functional data analysis of particle size distribution curves measured from vehicle exhaust emissions", submitted.

Department: Statistical Science and Biological Statistics and Computational BiologyTitle: Assistant ProfessorAddress: 1186 Comstock HallPhone: 607-255-1638email: giles.hooker@cornell.eduWebsite: www.bscb.cornell.edu/~hooker/

Peter Jackson

BiographyPeter Jackson is a Professor in the School of Opera-tions Research and Information Engineering. Born in Nipigon, Ontario, Canada, he received a B.A. in Economics with Mathematics in 1975 (University of Western Ontario), a M.Sc. in Statistics in 1978 (Stanford University), and a Ph.D. in Operations Research in 1980 (Stanford University). He has served at Cornell since 1980. He is Director of Graduate Studies for, and a former Director of, the Systems Engineering Program within the College of Engineering.

Jackson's research interests include planning and scheduling for integrated production, transportation and inventory management systems, supply chain management, and business modeling and data analy-sis. He has published in IIE Transactions, Journal of Manufacturing and Operations Management, Manage-ment Science, Mathematical Programming, Mathemat-ics of Operations Research, Naval Research Logistics Quarterly, and Operations Research. Professor Jackson has consulted with several companies in these areas, including Servigistics, General Motors, Cleveland Clin-ic, Xelus, Clopay Building Products, General Electric, Aeroquip, and Quaker Oats. He is the recipient of a General Motors Research and Development Innovation award in 2011 for a business process to optimize retail inventories.

Professor Jackson is also active in educational curriculum development for operations research and systems engineering. He is the recipient of several awards for curriculum innovation in addition to numerous stu-dent-voted awards for teaching excellence. He is the author of an introductory textbook to systems engineer-ing, Getting Design Right: A Systems Approach.

Research InterestsJackson's research interests include planning and scheduling for integrated production, transportation and inventory management systems, supply chain management, and business modeling and data analysis. Typi-cally, his research involves modeling a stochastic system, developing analytic approximations of the system performance, validating the approximations with simulation, and, finally, developing custom techniques to optimize the system performance. His broader interests, however, sometimes take him further afield in terms of research methodology. For example, working with faculty in Civil and Environmental Engineering and with systems engineering professionals at Corning, he developed an interview technique to score a compa-ny's use of systems engineering practices in a research and development setting.

Continued next page

Department: Operations Research and Information EngineeringTitle: ProfessorAddress: 218 Frank H T Rhodes HallPhone: 607-255-9122email: pj16@cornell.eduWebsite: people.orie.cornell.edu/jackson/new/

Selected Publications• Jackson, Peter, Jie Chen, John Muckstadt. 2011. "Exact Analysis of a Lost Sales Model Under Stuttering Poisson Demand". Operations Research Journal. • Jackson, Peter. 2009.Getting Design Right: A Systems Approach. : 366. CRC Press. • Jackson, Peter, F. Vanek, R Grzybowski. 2008"Systems Engineering Metrics and Applications in Product Development: A Critical Literature Review and Agenda for Further Research." Systems Engineering 11(2): 107-124. • Jackson, Peter, Kathryn Caggiano, John Muckstadt, J Rappold. 2007"Optimizing Service Parts Inventory in a Multi-Echelon, Multi-Item Supply Chain with Time-Based Customer Service Level Agreements." Operations Research 55(2): 303-318. • Jackson, Peter, Yuemeng Sun. 2010. "Hedging Strategy of Multi-Product Inventory Risk under Monetary Inflation." Paper presented at INFORMS Revenue Management Conference, June.

Selected Awards and Honors• GM R&D Innovation Award (General Motors) 2011 • Dorothy and Fred Chau MS '74 Excellence in Teaching Award (Cornell, College of Engineering) 2010 • ORIE Master of Engineering Teaching Award (Cornell, College of Engineering) 2010 • ORIE Undergraduate Outstanding Teaching Award (Cornell, College of Engineering) 2008

Robert A. Jarrow

BiographyProfessor Jarrow's teaching and research interests involve the study of mathematical finance. He is in-terested in derivatives, risk management, investments and asset pricing theory. Jarrow is currently engaged in research relating to the pricing of credit derivatives, liquidity risk, and risk management. He is a graduate faculty representative in four fields: management, eco-nomics, operations research and industrial engineer-ing, and applied mathematics.

Jarrow is on the advisory board of Mathematical Finance and he is an associate editor for numerous other finance journals. His research has won numer-ous awards including the Graham and Dodd Scrolls Award 2001, the CBOE Pomerance Prize in 1982, and the Ross Best Paper Award in 2008. In 1997, he was named IAFE Financial Engineer of the Year in recogni-tion of his research accomplishments. He is currently an IAFE senior fellow and an FDIC senior fellow. He is in the Fixed Income Analysts Society Hall of Fame, Risk Magazine's 50 member Hall of Fame, and listed in the Who's Who of Economics. He received Risk Maga-zine's Lifetime Achievement Award in 2009. He also serves on various corporate board of directors and advisory boards.

Selected Publications• Jarrow, Robert A.; Trautmann, Siegfried. "A Reduced Form Model for Warrant Valuation" The Financial Review 46.3 (2011): 413-425.• Jarrow, Robert A.; Protter, Philip E.. "Foreign Currency Bubbles" Review of Derivatives Research 14.1 (2011): 67-83.• Jarrow, Robert A.. "Credit Market Equilibrium Theory and Evidence: Revisiting the Structural versus Reduced Form Model Debate" Finance Research Letters 8.1 (2011): 2-7.• Jarrow, Robert A.; Xu, Liheng. "Credit Rating Accuracy and Incentives" Journal of Credit Risk 6.3 (2010): 133-151.• Jarrow, Robert A.; Oxman, Jeff; Yildirim, Yildiray. "The Cost of Operational Risk Loss Insurance" Review of Derivatives Research 13.3 (2010): 273-295.

Selected Awards and Honors• Clifford H. Whitcomb Faculty Fellowship 2011-12 • 12th Annual Bernstein Fabozzi/Jacobs Levy Award 2009-2010, Journal of Portfolio Management • Risk Magazine‘s Lifetime Achievement Award 2009 • Ross Best Paper Award 2008, Finance Research Letters • Center for Analytic Research Award 2006, Carnegie Mellon University.

Department: FinanceTitle: Ronald P. & Susan E. Lynch Professor of Investment ManagementAddress: 120 Sage Hall, JGSMPhone: 607-255-4729email: raj15@cornell.eduWebsite: www.johnson.cornell.edu/Faculty-And-Research/Profile.aspx?id=raj15

Jon M Kleinberg

BiographyJon Kleinberg is the Tisch University Professor in the Computer Science Department at Cornell University. His research focuses on issues at the interface of net-works and information, with an emphasis on the social and information networks that underpin the Web and other on-line media. He is a member of the National Academy of Engineering and the American Academy of Arts and Sciences, and serves on the Computer and Information Science and Engineering (CISE) Advisory Committee of the National Science Foundation, and the Computer Science and Telecommunications Board (CSTB) of the National Research Council. He is the recipient of MacArthur, Packard, and Sloan Founda-tion Fellowships, as well as the Nevanlinna Prize, Katayanagi Prize, ACM-Infosys Foundation Award, and National Academy of Sciences Award for Initia-tives in Research.

Selected Publications• Marvel, Seth, Jon M. Kleinberg, Robert David Kleinberg, Steven Strogatz. 2011. "Continuous-Time Model of Structural Balance." PNAS 108(5): 1771-1776. • Easley, David Alan, Jon M Kleinberg. 2010.Networks, Crowds, and Markets: Reasoning about a Highly Connected World. Cambridge University Press. • Danescu-Niculescu-Mizil, Cristian, Gueorgi Kossinets, Jon M. Kleinberg, Lillian Jane Lee. 2009. "How opinions are received by online communities: A case study on Amazon.com helpfulness votes (Proceedings of WWW)." Paper presented at Proceedings of WWW • Kleinberg, Jon M., Eva Tardos. 2005.Algorithm Design. Addison-Wesley. • Kleinberg, Jon M. 2000"Navigation in a small world." Nature 406(6798): 845-845.

Selected Awards and Honors• ACM-Infosys Foundation Award in the Computing Sciences 2009 • Member (National Academy of Engineering) 2008 • Member (American Academy of Arts and Sciences) 2007 • Rolf Nevanlinna Prize (International Mathematical Union) 2006 • John D. and Catherine T. MacArthur Foundation Fellowship 2005

Department: Computer ScienceTitle: Tisch University ProfessorAddress: 5134 Upson Hallemail: jmk6@cornell.eduWebsite: www.cs.cornell.edu/home/kleinber/

Robert David Kleinberg

BiographyRobert Kleinberg is an Assistant Professor of Computer Science at Cornell University. His research studies the design and analysis of algorithms, and their applica-tions to electronic commerce, networking, information retrieval, and other areas. Prior to receiving his doctor-ate from MIT in 2005, Kleinberg spent three years at Akamai Technologies, where he assisted in designing the world's largest Internet Content Delivery Network. He is the recipient of a Microsoft Research New Fac-ulty Fellowship, an Alfred P. Sloan Foundation Fellow-ship, and an NSF CAREER Award.

Research InterestsTheoretical Computer Science, Game Theory, Learning Theory, Combinatorial Optimization

Teaching InterestsDesign and Analysis of Algorithms

Selected Publications• Dobzinski, Shahar, Hu Fu, Robert David Kleinberg. 2011. "Optimal Auctions With Correlated Bidders Are Easy." Paper presented at Proceedings of the 43rd Annual ACM Symposium on Theory of Computing, June. • Marvel, Seth, Jon M. Kleinberg, Robert David Kleinberg, Steven Strogatz. 2011"Continuous-Time Model of Structural Balance." PNAS 108(5): 1771-1776. • Hartline, Jason D., Robert David Kleinberg, Azarakhsh Malekian. 2011. "Bayesian Incentive Compatibility Via Matchings." Paper presented at Proceedings of the 22nd Annual ACM-SIAM Symposium on Discrete Algorithms, January (1st Quarter/Winter). • Babaioff, M., Robert David Kleinberg, A. Slivkins 2010. "Truthful Mechanisms with Implicit Payment Computation." Paper presented at Proceedings of the 11th ACM Conference on Electronic Commerce (EC 2010), June. • Kleinberg, Robert David, Georgios Piliouras, Eva Tardos. 2009. "Multiplicative Updates Outperform Generic No-Regret Learning in Congestion Games." Paper presented at ACM Symposium on Theory of Computing, June.

Selected Awards and Honors• Best Paper Award at the ACM Conference on Electronic Commerce (EC) 2010 • Kenneth A. Goldman '71 Excellence in Teaching Award (Cornell University) 2009 • Alfred P. Sloan Research Fellowship 2008 • Cornell Association of CS Undergraduates, Faculty of the Year Award 2008 • Microsoft Research New Faculty Fellowship 2008

Department: Computer ScienceTitle: Assistant ProfessorAddress: 4138 Upson HallPhone: 607-255-9200email: robert.kleinberg@cornell.eduWebsite: www.cs.cornell.edu/~rdk/

Adrian Stephen Lewis

BiographyAdrian Lewis received his B.A., M.A., and Ph.D. de-grees from Cambridge University, U.K. After faculty positions at the University of Waterloo and Simon Fraser University in Canada, he joined Cornell Univer-sity in 2004 as a Professor in the School of Operations Research and Information Engineering, where he is currently Director. His research concerns nonsmooth optimization and variational analysis. He has authored nearly 100 refereed publications and a book, and he is Co-Editor of Mathematical Programming. He received the 1995 Aisenstadt Prize, the 2003 Lagrange Prize, and a 2005 Outstanding Paper Prize from SIAM, and he is a SIAM Fellow.

Research InterestsProfessor Lewis's research concerns the interplay between the mathematical theory of variational analy-sis and its practical application to concrete models in science and engineering, including the design and analysis of computational algorithms for nonsmooth optimization. He is particularly interested in optimiza-tion problems involving eigenvalues, such as robust control and pseudospectral sensitivity. Most recently his interests have turned to semi-algebraic geometry as a model for generic structure in nonsmooth optimiza-tion, leading to a fascinating blend of variational analysis, classical mathematics, numerical computation, and applied modeling.

Teaching InterestsAt the undergraduate level, Professor Lewis's primary focus has been on linear optimization: the formulation of linear programming models (using the modeling language AMPL), their solution by the simplex method, sensitivity analysis, duality, network programming, and applications such as resource allocation and produc-tion planning. Professor Lewis also teaches the mathematical foundations of linear optimization at the PhD level, as well as PhD courses on the theory and computational practice of nonlinear optimization, and on convex and variational analysis.

Service InterestsProfessor Lewis serves as Co-Editor of Mathematical Programming and as Associate Editor for Mathemat-ics of Operations Research, the SIAM Journal on Matrix Analysis, and the series SIAM/MPS Monographs on Optimization. He also served for a decade on the Editorial Board of the SIAM Journals on Optimization and (for several years) Control and Optimization. He recently ended five years as Treasurer of the Society for the Foundations of Computational Mathematics, in particular helping to lead the 2009 organization (and NSF funding) for a large-scale Special Semester at the Fields Institute in Toronto.

Department: Operations Research and Information EngineeringTitle: Director of ORIE, ProfessorAddress: 234 Frank H T Rhodes HallPhone: 607-255-9147email: aslewis@orie.cornell.eduWebsite: people.orie.cornell.edu/aslewis/

Continued next page

Selected Publications• Bolte, J., A. Daniilidis, Adrian S. Lewis. 2011"Generic optimality conditions of semi-algebraic convex programs." Mathematics of Operations Research 18. • Burke, J. V., D. Henrion, Adrian S. Lewis, M. L. Overton. 2006"Stabilization via nonsmooth, nonconvex optimization." IEEE Transactions on Automatic Control 51(11): 1760-1769. • Borwein, J M., Adrian S. Lewis. 2006.Convex Analysis and Nonlinear Optimization. (2nd): 310. New York, NY:Springer. • Lewis, Adrian S. 2003"Active sets, nonsmoothness and sensitivity." SIAM Journal on Optimization (13): 702-725. • Dontchev, A L., Adrian S. Lewis, R T Rockafellar. 2003"The radius of metric regularity." Transactions of the American Mathematical Society (355): 493-517.

Selected Awards and Honors• Fellow (Society for Industrial and Applied Mathematics (SIAM)) 2009 • Outstanding Paper Prize (Society for Industrial and Applied Mathematics(SIAM)) 2005 • Plenary Speaker (Fifth Conference on Foundations of Computational Mathematics, Santander) 2005 • Lagrange Prize for Continuous Optimization, (Mathematical Programming Society (MPS) and SIAM) 2003 • Aisenstadt Prize (Centre de Recherches Mathematiques, Montreal) 1995

Mark E. Lewis

BiographyProfessor Lewis received his undergraduate degree in Mathematics and Political Science from Eckerd College in 1992, his Master's degree in Theoretical Statistics from Florida State University in 1995, and a Ph.D. in Industrial Engineering from the Georgia Institute of Technology in 1998. After receiving his doctorate, Lew-is spent a year at the University of British Columbia as a postdoctoral fellow in the Center for Operations Excellence. He joined Cornell as an Associate Professor in 2005 after teaching Industrial and Operations Engi-neering at the University of Michigan.

Research InterestsBroadly speaking Professor Lewis is interested in dynamic control of service systems. Most often he uses the methodology of stochastic dynamic program-ming or Markov decision processes to analyze these problems. Along the way he has done fundamental research on the theory of MDPs. In the area of average cost MDPs on general state and action spaces he has studied convergence of discounted cost optimal values and policies and on a refinement of average cost theory called bias optimality he has studied implicit discount-ing. In terms of applications, Professor Lewis has considered routing in transportation systems, control of inventory systems and allocation of inter-switch handoffs in wireless communications. Despite his versatil-ity in the analysis of such systems his passion is for resource allocation in controlled queueing networks. In doing so, he has considered non-stationary networks, networks with limited capacity and those with varying service capabilities.

Teaching InterestsProfessor Lewis has been teaching courses in stochastic modeling and analysis at both the undergradu-ate and graduate levels. He has recently been asked to teach a course on probability theory as well. In the stochastic modeling courses, the use of Markov chains in modeling is the main focus. Applications include inventory/logistics, manufacturing/reliability and service systems. In fact, the aforementioned Master's of Engineering project on UAVs put into direct use some of the concepts that the students had learned in ORIE 3510. In terms of probability theory, not only does the course cover the classic material (Dynkin's π-λ theo-rem, construction of probability measures and convergence concepts), but it also trains the students on how to read and write mathematical proofs.

Department: Operations Research and Information EngineeringTitle: ProfessorAddress: 221 Frank H T Rhodes HallPhone: 607-255-0757email: mel47@cornell.eduWebsite: people.orie.cornell.edu/melewis/

Continued next page

Service InterestsProfessor Lewis is currently on the Meetings Committee for the Institute for Operations Research and Man-agement Science (INFORMS), is president and co-founder of the INFORMS Minority Issues Forum and is the president elect for the INFORMS Applied Probability Society. He co-chaired the 2009 INFORMS Applied Probability Society conference. He also co-edited a special issue (in 2009) on Queueing Analysis and Control for the journal Probability in the Engineering and Informational Sciences. He is a frequently requested public speaker in both engineering and business schools. Professor Lewis is the chair of the Ph.D. Admissions Com-mittee, organizes the Minority Issue Interest Group in the Cornell College of Engineering and is a member of the college-wide Strategic Oversight Committee.

Selected Publications• Down, Douglas G., Ger Koole, Mark E. Lewis. 2011"Dynamic Control of a Single Server System with Abandonments." Queueing Systems: Theory and Applications 67(1): 63-90. • Caudillo-Fuentes, Luz A., David L. Kaufman, Mark E. Lewis. 2010"A simple Heuristic for Load Balancing in Parallel Processing Networks with Highly Variable Service Time Distributions." Queueing Systems: Theory and Applications 64(2): 145-165. • Feinberg, E. A., Mark E. Lewis. 2007"Optimality inequalities for average cost Markov decision processes and the stochastic cash balance problem." Mathematics of Operations Research 32(4): 769-783. • Kaufman, D. L., Mark E. Lewis. 2007"Machine maintenance with workload considerations." Naval Research Logistics 54(7): 750-766. • Kaufman, D., H. S. Ahn, Mark E. Lewis. 2005"On the introduction of an agile, temporary workforce into a tandem queueing system." Queueing Systems 51(1-2): 135-171.

Selected Awards and Honors• Frontiers on Engineering Participant (National Academy of Engineering ) 2007 • Harold R. Johnson Diversity Award (University of Michigan) 2004 • Mentor of the Year (Sloan Foundation) 2003 • Presidential Early Career Award for Scientists and Engineers (PECASE) (National Science Foundation (NSF)) 2002 • George B. Dantzig Dissertation Award, Runner-up (INFORMS) 1999

Ping Li

EducationPh.D. in Statistics, Stanford UniversityMaster in Electrical Engineering, Stanford UniversityMaster in Computer Science, Stanford University

ProfilePing Li is currently an assistant professor in the De-partment of Statistical Science at Cornell University. In 2007, Ping Li graduated from Stanford University with his Ph.D. in Statistics and masters’ degrees in Comput-er Science and Electrical Engineering. Ping Li interned at Microsoft Research for three summers (2004, 2005, and 2006) and interned at the product group (Visual Studio) as an SDE in the summer of 2003. His research areas include randomized algorithms for processing massive datasets and statistical machine learning. Ping Li received the Office of Naval Research (ONR) Young Investigator Award in 2009.

Research InterestsMachine Learning, Randomized Algorithms for Large Data Sets

TeachingSpring 2012 Categorical DataFall 2008, Fall 2009 Theory of ProbabilitySpring 2009, Spring 2010, Theory of StatisticsSpring 2008, Spring 2009, Statistical ComputingFall 2012, Computationally Intensive Statistical Methods

Selected Publications• Ping Li, Art Owen, and Cun-Hui Zhang, One Permutation Hashing Neural Information Processing Systems (NIPS), 2012.• Ping Li, Anshumali Shrivastava, Joshua Moore, and Christian Konig, Hashing Algorithms for Large-Scale Learning, Neural Information Processing Systems (NIPS), 2011.• Ping Li and Christian Konig, Theory and Applications of b-Bit Minwise Hashing, Research Hightlights, Communications of the ACM, 2011. (Previous version appeared in WWW 2010)• Ping Li and Cun-Hui Zhang, A New Algorithm for Compressed Counting with Applications in Shannon Entropy Estimation in Dynamic Data, Conference on Learning Theory (COLT), 2011.• Ping Li, Christian Konig, and Wenhao Gui, b-Bit Minwise Hashing for Estimating Three-Way Similarities, Neural Information Processing Systems (NIPS), 2010.

Selected Awards and Honors• 2010 Prize in Yahoo! Learning to Rank Grand Challenge

Department: Statistical ScienceTitle: Assistant ProfessorAddress: 1192 Comstock HallPhone: 607-255-9813email: pingli@cornell.eduWebsite: www.stat.cornell.edu/~li/

David Scott Matteson

ResearchMy research interests include time series, spatial and spatio-temporal modeling, biostatistics, Bayesian sta-tistics, machine learning, semi-parametrics, point pro-cesses, and econometrics. I am particularly interested in high dimensional data analysis, which has become one of the most important areas of statistical research, with applications in many fields. While many recent efforts have attempted to incorporate mathematical and contextual constraints into analysis, most work on these difficult problems has focused on independent observations. I have found dependence to be a valu-able source of additional information, not merely an additional complexity, and I endeavor to make major contributions to this exciting new field.

As a statistician interested in applications, my primary research focus has involved the analysis of dependent data and the development of accompanying statisti-cal methodology. My research has been heightened by biological, environmental, financial and operational applications. My collaborations with scientists and other professionals continue to be mutually rewarding and personally enjoyable.

Department: Statistical ScienceTitle: Assistant ProfessorAddress: 1196 Comstock HallPhone: 607-255-6231email: dm484@cornell.eduWebsite: www.stat.cornell.edu/~matteson/

Andreea Minca

BiographyAndreea Minca joined the School of Operations Re-search and Information Engineering in August 2011. She received her PhD in Applied Mathematics form Pierre et Marie Curie University in Paris, France in 2011. In 2008, she earned a M.S. in Probability and Finance and the Diplôme de l'Ecole Polytechnique. During her PhD studies she was a member of the Mathematical Finance team at INRIA Rocquencourt, funded by a grant from the Natixis Foundation for Quantitative Research.

Her research is focused on the mathematical model-ing of default of financial institutions in the context of a banking system. During her thesis, she introduced a mathematical framework for understanding systemic risk via network analysis and tools drawn from ran-dom graph theory.

Her research interests include financial networks, control of epidemics in random graphs, credit risk and liquidity risk.

Select Publications• Rama Cont and Andreea Minca, Recovering portfolio default intensities implied by CDO quotes, Mathematical Finance, 2011.• Hamed Amini, Rama Cont and Andreea Minca. Resilience to contagion in financial networks, Preprint, 2010.• Hamed Amini, Rama Cont and Andreea Minca, Stress testing the resilience of financial networks, International Journal of Theoretical and Applied Finance, 2011.

Awards• Natixis Foundation of Quantitative Research PhD Scholarship, September 2008.• Full Scolarship from Ecole Polyechnique (2005 – 2008)• Merit Scholarship from Polytechnic University of Bucharest (2001 – 2005).• Third prize in National Mathematics Olympiad, Targu Mures, Romania, March 2001.

Department: Operations Research and Information EngineeringTitle: Assistant ProfessorAddress: 222 Rhodes HallPhone: 607-255-9133email: acm299@cornell.edu

John Anthony Muckstadt

BiographyJack Muckstadt is the Acheson-Laibe Professor of Engineering in the School of Operations Research and Information Engineering and a Stephen H.Weiss Presi-dential Fellow. Professor Muckstadt was the School's Director for nine years; he also established and was the first director of the Cornell Manufacturing Engineer-ing and Productivity Program. He is a co - director of Cornell's Institute for Disease and Disaster Prepared-ness. He was an officer in the U.S. Air Force and retired in 1983. He has consulted for many companies and governmental organizations. He holds a B.A. in Math-ematics from the University of Rochester and an M.A. in Mathematics and an M.S. and Ph.D. in Industrial Engineering from the University of Michigan.

Research InterestsProfessor Muckstadt conducts research in a variety of topics related to supply chain management. He has created mathematical models and algorithms designed to address strategic, tactical and operational problems faced by profit and non-profit organizations. The ap-plication areas include spare parts operations for the U S Air Force and companies like Xerox, distribution planning for oil companies, and fulfillment system and inventory planning for Amazon.com. As a member of the CDC's Board of Scientific Counselors, he has also studied several supply chain problems related to public health and emergency management. He has won awards for his research. He is a Fellow in the Institute for Operations Research and Management Science and an MSOM Fellow.

Teaching InterestsProfessor Muckstadt's teaching is in the areas of manufacturing systems and manufacturing logistics, sup-ply chain systems, and, most recently, response logistics for mass casualty events. He has won over a dozen teaching awards. To recognize his dedication and effectiveness as a teacher, he was named a Stephen H. Weiss Presidential Fellow.

Service InterestsDuring his tenure at Cornell University, Professor Muckstadt has been the School's Director for nine years, he established and was the first director of the Cornell Manufacturing Engineering and Productivity Program, and is a co - director of Cornell's Institute for Disease and Disaster Preparedness. He has been active in gov-ernment service and presently serves on a Board of Scientific Counselors to the CDC

Continued next page

Department: Operations Research and Information EngineeringTitle: Acheson/Laibe Professor of Business Management and LeadershipAddress: 286 Frank H T Rhodes HallPhone: 607-255-9123email: jam61@cornell.eduWebsite: people.orie.cornell.edu/jack/

Selected Publications• Muckstadt, John Anthony, Amar Sapra. 2010.Principles of Inventory Management. XVIII(1): 339. New York, NY:Springer. • Huh, W. T., G. Janakiraman, John Anthony Muckstadt, Paat Rusmevichientong. 2009"Asymptotic Optimality of Order-Up-To Policies in Lost Sales Inventory Systems." Management Science 55(3): 404-420. • Caggiano, K. E., P. L. Jackson, John Anthony Muckstadt, J. A. Rappold. 2007"Optimizing service parts inventory in a multiechelon, multi-item supply chain with time-based customer service-level agreements." Operations Research 55(2): 303-318. • Caggiano, K. E., John Anthony Muckstadt, J. A. Rappold. 2006"Integrated real-time capacity and inventory allocation for reparable service parts in a two-echelon supply system." M&SOM-Manufacturing & Service Operations Management 8(3): 292-319. • Muckstadt, John Anthony. 2005.Analysis and Algorithms for Service Parts Supply Chains. XVII: 277. New York, NY:Springer.

Selected Awards and Honors• Weiss Presidential Fellow 2010 • INFORMS Fellow (INFORMS) 2009 • MSOM Fellow (MSOM/ INFORMS) 2009 • Outstanding Reserve Officer (US Air Force Logistics Command) 1981 • Outstanding Teaching Award (Recipient of American Institute of Industrial Engineers ) 2004

Pierre Patie

BiographyPierre Patie is an Associate Professor in the School of Operations Research and Information Engineering (ORIE) of Cornell University. He is currently on leave from the Department of Mathematics at Université Li-bre de Bruxelles. He got his M.S. Degree in Mathemati-cal Engineering from both, the Swiss Federal Institute of Technology, Lausanne and Ecole Polytechnique, Paris and his Ph.D. in mathematics from the Swiss Federal Institute of Technology, Zurich. His research interests lie in the study of stochastic processes and their applications in financial and insurance mathemat-ics, with an emphasis to Markov processes and their connections to functional analysis.

Research InterestsProfessor Patie works on problems located at the interplay between probability theory and functional analysis and their applications to financial and insur-ance mathematics. An important theme of research is the study of the first exit time of a possibly time-dependent domain and additive functionals of special substantial classes of Markov processes, such as Lévy processes and completely asymmetric Markov pro-cesses. These problems reveal several interesting connections with some classical problems in analysis, such as properties and behavior of green functions, spectral theory of non-self-adjoint operators and the study of special functions. On the other hand, these problems find applications in many fields of sciences such as biology, neurology, physics and in economics. He works on applications in application in risk theory and in financial mathematics such as the pricing of exotic options.

Selected Publications• Patie P. and Simon T. (2012). Intertwining certain fractional operators, Potent. Anal., 36: 569-587.• Pardo J.-C., Patie P. and Savov M. (2012). A Wiener-Hopf type factorization for the exponential functional of Lévy processes, J. London Math. Society 86(3): 930-956.• Patie P. (2012). Law of the absorption time of positive self-similar Markov processes, Ann. Probab.,40(2):765-787.• Kyprianou A.E. and Patie P. (2011). A Ciesielski-Taylor type identity for positive self-similar Markov processes, Ann. Inst. H. Poincaré Probab. Statist., 47(39): 917-928.• Alili L. and Patie P. (2010). Boundary crossing identities for diffusions having the time inversion property, J. Theor. Prob., 23(1), 65-84.

Department: Operations Research and Information EngineeringTitle: Associate ProfessorAddress: 219 Frank H T Rhodes HallPhone: 607-255-9130email: pp396@cornell.edu

James Renegar

BiographyJames Renegar received his Ph.D. in Mathematics from the University of California at Berkeley in 1983, after earning a B.S. from Rice University, Houston, TX, in 1978. He is a Professor in the School of Operations Research and Information Engineering, where he has been on the Faculty since 1987, and served as Director 2004-09. In his research, Renegar focuses on develop-ing mathematical foundations for a variety of algo-rithmic issues pertaining to continuous optimization and to the numerical solution of systems of algebraic nonlinear equations. This includes creating new fami-lies of algorithms possessing novel properties, as well as deepening our understanding of existing algorithms and modeling techniques - especially our understand-ing of the effects of round-off errors and imprecise data.

Research InterestsProfessor Renegar's primary research focus is in continuous optimization but he is interested more generally in a range of algorithmic problems possess-ing interplay between numerical analysis and algebra (e.g., approximating roots of polynomials, decision and quantifier elimination methods for the first-order theory of the reals, interior-point methods for algebraic convex optimization problems). He has laid theoretical foundations for round-off error analysis of algorithms for convex optimization. Currently he is pursuing hyperbolic programming, where he is devising algorithms that generalize interior-point methods. He has a growing interest in optimization applications in finance.

Teaching InterestsProfessor Renegar teaches a variety of courses on optimization, including ones that introduce students to basic optimization modeling techniques and algorithms, another that gives students dexterity with cutting-edge applications of optimization in finance, and advanced ones in which students fully master the intrica-cies of mathematically-sophisticated optimization theory.

Service InterestsProfessor Renegar has organized many workshops, especially for the Society for Foundations of Computa-tional Mathematics, of which he was a founding member, served as treasurer for three terms, and has long been on the board of directors. He has been an associate editor for SIAM Journal on Optimization, was chair of the 2002 INFORMS Lanchester Prize committee, and currently is committee chair for the INFORMS Opti-mization Society's Prize for Young Researchers. He was Cornell ORIE Director from 2004 until 2009.

Continued next page

Department: Operations Research and Information EngineeringTitle: ProfessorAddress: 224 Frank H T Rhodes HallPhone: 607-255-9142email: jr43@cornell.edu

Selected Publications• Renegar, James. 2001. "A Mathematical View of Interior-Point Methods for Convex Optimization". Philadelphia, PA: • Renegar, James. 1990. "Computational complexity of solving algebraic formulae". 1595-1606. • Renegar, James. 2010"Central Swaths - a generalization of the central path." Journal of Foundations of Computational Mathematics. • Renegar, J. 2006"Hyperbolic programs, and their derivative relaxations." Foundations of Computational Mathematics 6(1): 59-79. • Pena, J., J. Renegar. 2000"Computing approximate solutions for convex conic systems of constraints." Mathematical Programming 87(3): 351-383.

Selected Awards and Honors• "Sonny Yau '72" Teaching Award (Cornell College of Engineering ) 2001 • Semi-Plenary Speaker (17th International Symposium on Mathematical Programming) 2000 • "Sonny Yau '72" Teaching Award (Cornell College of Engineering ) 1998 • "Outstanding Professor in Operations Research" (Cornell Chapter of Tau Beta Pi ) 1997 • "Professor of the Year" Teaching Award (Cornell Chapter of the American Institute of Industrial Engineers ) 1997

Sidney Ira Resnick Department: Operations Research and Information EngineeringTitle: Lee Teng-Hui Professor of EngineeringAddress: 284 Frank H T Rhodes HallPhone: 607-255-1210email: sir1@cornell.eduWebsite: people.orie.cornell.edu/sid/

BiographySidney Resnick joined the Cornell faculty in 1987 after nine years at Colorado State University, six years at Stanford University, and two years at the Technion, in Haifa, Israel. He has held visiting appointments at the University of Amsterdam and the Amsterdam Math-ematics Center; the Australian National University and CSIRO, in Canberra, Australia; the Technion in Israel (as a Lady Davis Fellow); Sussex University, in Brigh-ton, UK, Erasmus University Rotterdam, ETH Zurich, Department of Statistics, UNC, Chapel Hill; Columbia University; Samsi, Research Triangle Park, NC; Tech-nical University Munich (as John Von Neuman Visit-ing Professor). Resnick is a fellow of the Institute of Mathematical Statistics, and while at Colorado State was an Oliver Pennock Distinguished Service Award winner. He is a founding associate editor of Annals of Applied Probability, and a current associate editor of Stochastic Models, Extremes, Stochastic Processes and their Applications and The Mathematical Scientist. He is a former associate editor of Journal of Applied Probability. He served a three-year term on the Council of the Institute of Mathematical Statistics and served on their ad hoc committee on electronic publishing. He is currently an editor for Birkhauser, Boston serving on the boards of the Progress in Probability and Progress in Probability and Its Applications series and also serves on the editorial board of the Springer series Operations Research and Financial Engineering. His BS is from Queens College, NYC and his PhD is from Purdue. Resnick concluded a five year term as Director of Cornell's School of Operations Research and Information Engineering in June 2004. Professor Resnick has authored or coauthored 160 papers and four books.

Research InterestsProfessor Resnick's professional interests center in applied probability and cross the boundary into statistics. Past foci include modeling questions for queues, storage facilities, extremes, data networks, risk estimation and estimation problems for tails and non-standard time series models. A recurrent theme is influence of tails, especially heavy tails where large values shock the system. Heavy tailed modeling has become increas-ingly important in data network modeling and finance. In network modeling, heavy tailed file sizes are the explanation for observed long range dependence in network traffic and in finance, extreme value and heavy tailed methods offer methods for calculating value at risk. The analytic basis for heavy tailed modeling is the theory of regularly varying functions; the probabilistic basis for modeling turns out to rest on stochas-tic point processes. Tail estimation problems generally require estimating beyond the range of the data and require a good understanding of probability, stochastic processes and statistics in order to do sensible things. Likewise, good data network research utilizes applied probability, statistics, simulation and optimization.

Continued next page

Department: Operations Research and Information EngineeringTitle: ProfessorAddress: 284 Frank H T Rhodes HallPhone: 607-255-1210email: sir1@cornell.edu

Teaching InterestsProfessor Resnick's teaching concentrates broadly on applied probability and statistics and often there is emphasis on the interplay between the two. In the past year Professor Resnick has taught ORIE 6540 (Ad-vanced Stochastic Processes; elective course) and ORIE 3510 (junior level required introduction to stochastic modeling). In previous years he has taught PhD probability (6510), stochastic processes (6500), PhD introduc-tion to Statistics (6700), quantitative risk analysis, time series analysis, extreme value analysis, introduction to statistical analysis (sophomore level). Professor Resnick has authored two PhD level texts which are often used in ORIE 6500 and 6510.

Service InterestsProfessor Resnick serves as associate editor of three leading applied probability journals and one generalist mathematics publication. He is a founding member of the editorial board of the Springer Series in Opera-tions Research and Financial Engineering and on the editorial board of two probability series for Birkhauser. This past year he served on the program committee of the Newton Institute, Cambridge. He is often asked for advice on tenure reviews and re-appointments as well as hiring decisions.

Selected Publications• Resnick, Sidney Ira. 2007.Heavy Tail Phenomena: Probabilistic and Statistical Modeling. (XIX): 406. • Resnick, Sidney Ira. 1998.A Probability Path. (1st): 230. Boston, MA:Springer/ Birhauser. • Resnick, Sidney Ira. 1997"Heavy tail modeling and teletraffic data." Annals of Statistics 25(5): 1805-1849. • Resnick, Sidney Ira. 1992.Adventures in Stochastic Processes. : 640. Boston, MA:Springer/ Birkhauser. • Resnick, Sidney Ira. 1987.Extreme Values, Regular Variation and Point Processes. (1): 320. New York, NY:Springer.

Selected Awards and Honors• Distinguished Affiliated Professor (Technische Universität München) 2011 • Invited Tutorial (INFORMS Applied Probability Society Annual Meeting 2011) 2011 • Fellow of the Institute of Mathematical Statistics (Institute of Mathematical Statistics) 2010 • Designated Lee Teng-Hui Professor in Engineering 2008 • Best Paper in 2003 in Stochastic Models (Marcel Neuts Award) 2003

David Ruppert

BiographyDavid Ruppert is Andrew Schulz Jr. Professor of Engi-neering, School of Operations Research and Informa-tion Engineering, and Professor of Statistical Science, Cornell University. He received a BA in Mathematics from Cornell University in 1970, an MA in Mathemat-ics from the University of Vermont in 1973, and a PhD in Statistics and Probability from Michigan State University in 1977. He was Assistant and then Associ-ate Professor of Statistics at the University of North Carolina, Chapel Hill, from 1977 to 1987. He is a Fellow of the ASA and IMS and received the Wilcoxon Prize in 1986. Professor Ruppert was named "Highly cited" researcher by ISIHighlyCited.com and was ranked 21st in mathematics by journal citations. He has had 25 PhD students, many of them now leading researchers. Pro-fessor Ruppert has worked on stochastic approxima-tion, transformations and weighting in regression, and smoothing. His current research focuses on measure-ment error models, splines, semiparametric regression, and environmental statistics. He has published over 100 articles in refereed journals and has published five books, Transformation and Weighting in Regression, Measurement Error in Nonlinear Models (first and second editions), Semiparametric Regression, Statistics and Finance: An Introduction, and Statistics and Data Analysis for Financial Engineering.

Research InterestsProfessor Ruppert's current research is on calibration and uncertainty analysis, semiparametric regression, splines in statistics, functional data analysis,and biostatistics. He has had continuous external research fund-ing since 1978 with grants from NSF, NIH, and EPA. He has published over 100 research papers.

Teaching InterestsIn the past, Professor Ruppert has taught courses on regression, experimental design, measurement error, Taguchi methods, nonparametric estimation, time series, data mining, mathematical statistics, rank tests, statistical methods for risk analysis, and asymptotic theory. Most recently, he has taught a PhD course on Bayesian statistics and has developed three new courses for undergraduates and master's students: ORIE 3120, Industrial Data and Systems Analysis (developed and taught jointly with Peter Jackson and using their lecture notes); ORIE 4630, Operations Research Tools for Financial Engineering (which uses Professor Rup-pert's textbook, Statistics and Finance: An Introduction); and ORIE 5640, Statistics for Financial Engineering (which uses Professor Ruppert's textbook Statistics and Data Analysis for Financial Engineering).

Department: Operations Research and Information EngineeringTitle: Andrew Schultz Jr. Professor of Industrial EngineeringAddress: 225 Frank H T Rhodes HallPhone: 607-255-9136email: dr24@cornell.eduWebsite: people.orie.cornell.edu/davidr/

Continued next page

Service InterestsProfessor Ruppert is the editor of the Electronic Journal of Statistics which is published jointly of the Institute of Mathematical Statistics and the Bernoulli Society, the two leading societies in mathematical statistics and probability. He is a member of the Harvard P01 External Advisory Committee. At Cornell, he was Chair of the Spring 2009-Fall 2010 Search Committee in the Department of Statistical Science; this search resulted in the recent hiring of two distinguished senior statistics. Also in DSS, he is Chair of the Distinguished Alumni Award Committee and a member of the MPS Review Committee.

Selected Publications• Ruppert, David. 2010.Statistics and Data Analysis for Financial Engineering. New York, NY:Springer. • Carroll, R., David Ruppert, L. Stefanski, C Crainicanu. 2006.Measurement Error in Nonlinear Models, A Modern Perspective, 2nd Edition. (2): 488. Chapman and Hall/CRC. • Ruppert, David. 2004.Statistics and Finance: An Introduction. New York, NY:Springer. • Ruppert, David, D. Wand, R Carroll. 2003.Semiparametric Regression. (12): 404. Cambridge University Press. • Bliznyuk, Nikolay, David Ruppert, Christine Ann Shoemaker. 2011"Bayesian Inference Using Efficient Interpolation of Computationally Expensive Densities with Variable Parameter Costs." Journal of Computational and Graphical Statistics.

Selected Awards and Honors• Ranked #21 by citations in mathematics (Essential Science Indicators) 2010 • "Highly cited" researcher (ISIHighlyCited.com) 2010 • Fellow of the American Statistical Association (American Statistical Association) 1989 • Fellow of the Institute of Mathematical Statistics (Institute of Mathematical Statistics) 1986 • Wilcoxon prize for best practical applications paper (Technometrics) 1986

Gennady Samorodnitsky

BiographyGennady Samorodnitsky received his B.S. in 1978 from the Moscow Steel and Alloys Institute, USSR, his M.S. and his D. Sc. 1986 from Technion, Israel in 1983. He joined the School of Operations Research and Industri-al Engineering in 1988. After completing his doctorate, Samorodnitsky spent two years as a visiting professor, first at the University of North Carolina at Chapel Hill and then at Boston University.

Research InterestsHis research interests lie both in probability theory and in its various applications. A very important area is that of stochastic modeling, and he is especially inter-ested in "non-standard" models, in particular those exhibiting heavy tails and/or long-range dependence. These models behave very differently from the "usual" models that are typically based on Gaussian or Markov stochastic processes. Both heavy tails and long-range dependence are observed in financial processes, tele-traffic processes and many other processes. Since many classical statistical tools break down in the presence of long-range dependence and/or absence of Gaussianity, it is very important to understand how "non-standard" models behave, how one simulates them, how one estimates their parameters, and how one predicts their behavior in the future. He is interested in interaction of toplogy with probability theory; applications are, among others, in medicine and cosmology. He is looking closely, in particular, at certain financial and queue-ing models. Other areas of interest include self-similar (fractal-like) stochastic processes, extrema of sto-chastic processes, zero-one laws, positive and negative dependence in stochastic processes, stable and other infinitely divisible processes and level crossings of stochastic processes.

Teaching InterestsProfessor Samorodnitsky's teaching focuses on courses in probability and stochastic processes. He also teaches some finance courses and some statistics courses.

Continued next page

Department: Operations Research and Information EngineeringTitle: ProfessorAddress: 220 Frank H T Rhodes HallPhone: 607 255-9141email: gs18@cornell.eduWebsite: people.orie.cornell.edu/gennady/

Selected Publications• Grabchak, M., Gennady Samorodnitsky. 2010"Do Financial returns have finite or infinite variance? A paradox and an explanation." Quantitative Finance (10): 883-893. • Samorodnitsky, Gennady, H. Hauksson, M. Dacorogna, T. Domenig, U Muller. 2001"Multivariate extremes, aggregation and risk estimation." Quantitative Finance 1(1): 79-95. • Jessen, AH, T. Mikosch, Gennady Samorodnitsky. 2011"Prediction of outstanding payments in a Poisson cluster model." Scandinavian Actuarial Journal. • Adler, R., Gennady Samorodnitsky, J taylor. 2011"High level excursion set geometry for non-Gaussian infinitely devisible random fields." Annals of Probability. • Demichel, Y., A. Estrade, M. Kratz, Gennady Samorodnitsky. 2011"How fast can the Chord-Length Distribution Decay." Advances in Applied Probability.

Selected Awards and Honors• Wolf Foundation Scholarship (Wolf Foundation) 2000 • Fellowship in the Institute of Mathematical Statistics 2000 • Chaim Weizmann Fellowship 1987 • Chaim Weizmann Fellowship 1986 • First Annual Applied Probability Lecturer by the Applied Probability Trust (Applied Probability Trust) 2009

David B Shmoys

BiographyDavid Shmoys obtained his Ph.D. in Computer Sci-ence from the University of California at Berkeley in 1984. He has faculty appointments in both the School of Operations Research and Information Engineering and the Department of Computer Science. Shmoys' research has focused on the design and analysis of ef-ficient algorithms for discrete optimization problems. His work has highlighted the central role that linear programming plays in the design of approximation algorithms for NP-hard problems. His current work includes the application of discrete optimization tech-niques to several issues in computational sustainability, as well as in the development of approximation algo-rithms for stochastic models of clustering, inventory, and related problems in logistics.

Research InterestsShmoys has made fundamental contributions to the area of approximation algorithms for discrete optimi-zation problems, having given the first constant-per-formance guarantees for a wide range of problems in scheduling, clustering, and supply chain management. His work on polynomial-time approximation schemes for scheduling problems introduced techniques that have subsequently been applied to a variety of other settings. His current work includes the application of discrete optimization techniques to the emerging area of computational sustainability, as well as in the development of approximation algorithms for stochastic optimization models.

Teaching InterestsProfessor Shmoys teaches classes in the area of optimization, algorithm design, and the mathematical model-ing of applications with an optimization component. He has developed a series of integrated weekly compu-tational labs within the course ENGRI 1101 Engineering Applications of Operations Research, and regularly teaches a wide variety of optimization courses at all levels.

Service InterestsDavid Shmoys currently serves as Vice Chair of the IEEE Technical Committee on Mathematical Founda-tions of Computing, and is on the Scientific Committee for the Mathematics of the Planet Earth, 2013. He is currently an Associate Editor of Mathematics of Operations Research, and an Advisory Editor for Surveys in Operations Research and Management Science, and has also been on the editorial boards of ORSA J. on Com-puting, Operations Research, Mathematical Programming, Discrete Applied Mathematics, Communications of the ACM, SIAM J. on Computing, and SIAM J. on Discrete Mathematics, for which he served as Editor-in-Chief. Professor Shmoys has served on numerous program and prize committees associated with SIAM, ACM, IEEE, and INFORMS.

Department: Operations Research andInformation EngineeringTitle: ProfessorAddress: 231 Frank H T Rhodes HallPhone: 607-255-9146email: dbs10@cornell.eduWebsite: people.orie.cornell.edu/shmoys/

Continued next page

Selected Publications• Williamson, David P., David B Shmoys. 2011.The Design of Approximation Algorithms. : 520. Cambridge University Press. • Shmoys, David B., Chaitanya Swamy. 2006"An approximation scheme for stochastic linear programming and its application to stochastic integer programs." Journal of the ACM 53(6): 978-1012. • Shmoys, David B., Eva Tardos, Karen Aardal. 1997. "Approximation Algorithms for Facility Location Problems". 265-274. • Hall, Leslie A., Andreas S. Schulz, David B. Shmoys, Joel Wein. 1997"Scheduling to minimize average completion time: off-line and on-line approximation algorithms." Mathematics of Operations Research 22(3): 513-544. • Lenstra, Jan Karel, David B. Shmoys, Eva Tardos. 1990"Approximation algorithms for scheduling unrelated parallel machines." Mathematical Programming (46): 259-271.

Selected Awards and Honors• Sonny Yau Award for Excellence in Teaching (Cornell College of Engineering) 2003 • Fellow (Association for Computing Machinery (ACM)) 2002 • Sonny Yau Award for Excellence in Teaching (Cornell College of Engineering) 1998 • Presidential Young Investigator (National Science Foundation (NSF)) 1987 • Phi Beta Kappa Prize (Princeton University) 1981

Christine Ann Shoemaker

Research InterestsProf. Shoemaker's research focuses on finding cost-effective, robust solutions for environmental problems by using optimization, modeling and statistical analy-ses. This includes development of general purpose, numerically efficient nonlinear and global optimization algorithms utilizing high performance computing and applications to data from complex, nonlinear environ-mental systems. Her applications areas include physi-cal and biological groundwater remediation, pesticide management, ecology, carbon sequestration, and sur-face water pollutant transport in large watersheds. This analysis has resulted in improved policies for environ-mental remediation and protection.

Selected Publications• Regis, Rommel, Christine Ann Shoemaker. 2011"Global Optimization Using a Stochastic Radial Basis Function Algorithm with Dynamic Coordinate Search,." Journal of Global Optimization. • Bliznyuk, Nikolay, David Ruppert, Christine Ann Shoemaker. 2011"Bayesian Inference Using Efficient Interpolation of Computationally Expensive Densities with Variable Parameter Costs." Journal of Computational and Graphical Statistics. • Shoemaker, Christine Ann, Stefan M Wild. 2011"Global Convergence of Radial Basis Functions Trust Region Algorithms." SIAM Optimization Journal. • Chu, J C., Y. Zhang, H. Whang, C A. Zhou, Christine Ann Shoemaker. 2011"Watershed Rainfall Data Recovery Approach in Distributed Hydrological Models: The Application of SWAT Model in the Hali River Catchment." Hydrologic Processes. • Regis, R G., Christine Ann Shoemaker. 2011"A Quasi-Multistart Framework for Global Optimization of Expensive Functions using Response Surface Models." Computers and Operations Research.

Selected Awards and Honors• Distinguished (Honorary) Member (American Society of Civil Engineers) 2006 • Fellow (American Geophysical Union) 2003 • Joseph P. Ripley Professor of Engineering (Cornell University) 2002 • Humboldt Research Prize (A. von Humboldt Foundation ) 2001 • Julian Hinds Award (American Society of Civil Engineers ) 1999

Department: Civil and Environmental EngineeringTitle: Joseph P. Ripley Professor of EngineeringAddress: 210 Hollister HallPhone: 607-255-9233email: cas12@cornell.eduWebsite: gradeducation.lifesciences.cornell.edu/faculty/individual5813

Robert L. Strawderman

BiographyI am a professor in the Departments of Biological Sta-tistics and Computational Biology (BSCB) and Statisti-cal Science at Cornell University. I graduated in 1988 with a BA in Mathematics from Rutgers College, the main undergraduate college of Rutgers University pri-or to its restructuring as part of the new School of Arts and Sciences. I earned both my masters and doctoral degrees in Biostatistics at Harvard University. Before coming to Cornell, I was a faculty member in the De-partment of Biostatistics at the University of Michigan. I am part of a family tradition in statistics: my father is a Professor of Statistics at Rutgers, and my wife is a consulting statistician in the Division of Nutritional Sciences at Cornell.

My major research area is survival analysis, with a focus on problems involving recurrent event data and risk prediction. More generally, I am interested in sta-tistical inference for point process data; outcome pre-diction in medicine, epidemiology and public health; evaluating the cost and quality of health care; demog-raphy and population studies; asymptotics (theory and approximation); and, various problems in statistical computing. Recently, my students have worked on computational methods for analyzing high dimensional datasets, Bayesian approaches to the semiparametric proportional hazards model, smooth methods of esti-mation for the accelerated failure time model, GEE methods for recurrent event data, models for correlated bivariate point processes, wavelet-based methods for analyzing aCGH data, and various other problems. I am currently (or have recently) engaged in a variety of collaborative activities, including cardiology, cancer risk prediction, health services research, social science research in public health and nutrition, watershed modeling, genomics, genetic epidemiology, and veterinary medicine. I am presently involved in the Cornell Population Center (CPC) as the director of its statistics core. The CPP is an interdisciplinary group of Cornell researchers with interests in demography and population research.

In terms of noteworthy professional and university-level activities, I have continuously served as an Asso-ciate Editor for JASA (Theory & Methods) since 1997. I also serve as an Associate Editor for The Electronic Journal of Statistics and recently stepped down from a three-year term as a moderator for arXiv ( stat.TH). I am a Fellow of the ASA and also a member of both ENAR and IMS. At Cornell, I am the Director of Gradu-ate Studies for the fields of Statistics and Biometry. In addition to these two fields, I am also a member of the major field Operations Research and Information Engineering and minor fields of Demography and Epide-miology.

Department: Biological Statistics and Computational Biology / Statistical ScienceTitle: ProfessorAddress: 1172 Comstock HallPhone: 607-255-1642email: r.strawderman@cornell.eduWebsite: www.bscb.cornell.edu/~strawderman

Selected Publications• Strawderman RL, Wells MT (2011). On hierarchical prior specifications and penalized likelihood. To appear in Contemporary Developments in Bayesian Analysis and Statistical Decision Theory: A Festschrift for William E. Strawderman. IMS Collections, Volume 8. • Schifano E, Strawderman RL, Wells MT (2010). MM Algorithms for minimizing nonsmoothly penalized objective functions. Electronic Journal of Statistics. 4: 1258-1299.• Sharef E, Strawderman RL, Ruppert D, Cowen ME, Halasyamani L (2010). Adaptive Bayesian adaptive B-spline estimation in proportional hazards frailty models. Electronic Journal of Statistics. 4: 606-642.• Liu L, Strawderman RL, Cowen ME, Shih T (2010). A flexible two-part random effects model for correlated medical cost data. Journal of Health Economics. 29: 110-123. • Johnson LM and Strawderman RL (2009). Induced smoothing for the semiparametric accelerated failure time model: asymptotics and extensions to clustered data. Biometrika, 96: 577-590.

Eva Tardos

BiographyEva Tardos received her Dipl.Math. in 1981, and her Ph.D. 1984, from Eötvös University, Budapest, Hun-gary. She was Chair of the Department of Computer Science at Cornell University 2006-2010. She has been elected to the National Academy of Engineering and the American Academy of Arts and Sciences, and is the recipient of Packard, Sloan Foundation, and Guggen-heim fellowship, an ACM Fellow, INFORMS fellow; and has received the Fulkerson Prize, and the Dantzig prize. She was editor editor-in-Chief of SIAM Journal of Computing 2004-2009, and is currently editor of several other journals: Journal of the ACM, Theory of Computing, and Combinatorica.

Tardos's research interest is algorithms and algorith-mic game theory. Her work focuses on the design and analysis of efficient methods for combinatorial-optimization problems on graphs or networks. She is most known for her work on network-flow algorithms, approximation algorithms for network flows, cut, and clustering problems. Her recent work focuses on algo-rithmic game theory, an emerging new area of design-ing systems and algorithms for selfish users

Selected Publications• Tardos, Eva, Renato Paes Leme. 2010. "Pure and Bayes-Nash Price of Anarchy for Generalized Second Price Auction." Paper presented at Annual IEEE Symposium on Foundations of Computeer Science, November. • Kleinberg, Robert David, Georgios Piliouras, Eva Tardos. 2009. "Multiplicative Updates Outperform Generic No-Regret Learning in Congestion Games." Paper presented at ACM Symposium on Theory of Computing, June. • Kleinberg, Robert David, G. Piliouras, Eva Tardos. 2009. "Multiplicative Updates Outperform Generic No-Regret Learning in Congestion Games." Paper presented at ACM Symposium on Theory of Computing • Kleinberg, Jon M., Eva Tardos. 2005.Algorithm Design. Addison-Wesley. • Blume, Larry, David Easley, Robert David Kleinberg, Jon M. Kleinberg, Eva Tardos. 2011. "Network Formation in the Presence of Contagious Risk." Paper presented at ACM Conference on Electronic Commerce, June.

Selected Awards and Honors• Van Wijngaarden Award (CWI, Netherlands) 2011 • Dantzig Prize 2006 • Fellow (American Academy of Arts and Sciences) • Member (National Academy of Engineering) • Recipient, Packard Fellowship

Department: Computer ScienceTitle: Jacob Gould Schurman ProfessorAddress: 4119 Upson HallPhone: 607 255-0984email: eva@cs.cornell.eduWebsite: www.cs.cornell.edu/people/eva/eva.html

Michael Jeremy Todd

BiographyMichael Todd received his B.A. from Cambridge Uni-versity, UK, in 1968, and his Ph.D. from Yale Universi-ty, New Haven, Connecticut, in 1972. He joined Cornell University in 1973, where he is currently the Leon C. Welch Professor of Operations Research and Informa-tion Engineering. The focus of his research has been on the development and analysis of algorithms for con-tinuous optimization problems, including simplicial algorithms for fixed-point problems, simplex and ellip-soid algorithms for linear programming, interior-point methods for semidefinite and cone programming, and first-order methods for ellipsoid optimization prob-lems.

Research InterestsIn general, Professor Todd is concerned with algo-rithms for certain classes of convex programming problems and their computational complexity. Ex-amples include pivoting algorithms for quadratic programming and linear complementarity problems, the ellipsoid algorithm for linear and convex program-ming, interior-point methods for linear and semidefi-nite and more general conic programming problems, and first-order methods for certain ellipsoid optimization problems. He has also, with two former graduate students, produced the widely-used SDPT3 software package for linear, second-order, and semidefinite pro-gramming problems. Work continues on ellipsoid optimization problems, on questions in robust optimiza-tion, and on trying to understand the excellent real-world performance of interior-point methods.

Teaching InterestsProfessor Todd used both Videonote and lecture notes posted on the course home page for ORIE 3300/5300, despite some concerns with losing attendance. Students really appreciated being able to catch up on missed lectures due to job interviews, etc., and attendance suffered only slightly. Lectures covered the theory of lin-ear programming and algorithms for solving these problems, while most of the recitations provided hands-on experience with using the algebraic modeling language AMPL to represent real-life problems; AMPL models were also covered in the lectures, to stress the importance of modeling. Problem sets and exams dealt with both aspects of the course. ORIE 6310 dealt with extensions of linear programming, with a focus on complexity issues, including instances requiring exponential time for pivoting algorithms, expected poly-nomial-time pivoting algorithms, the diameter of polyhedra, and the informational complexity of nonlinear programming.

Department: Operations Research and Information EngineeringTitle: Leon C. Welch ProfessorAddress: 229 Frank H T Rhodes HallPhone: 607-255-9135email: mjt7@cornell.eduWebsite: people.orie.cornell.edu/miketodd/index2.html

Continued next page

Service InterestsMichael Todd is currently the chair of the SIAM Activity Group on optimization, as well as the managing editor for the journal Foundations of Computational Mathematics. He was previously the editor-in-chief of Mathematical Programming and the chair of the Society for the Foundations of Computational Mathematics, and has served on the editorial boards of several journals and book series.

Selected Publications• Ahipasaoglu, S. D., P. Sun, Michael Jeremy Todd. 2008, "Linear convergence of a modified Frank-Wolfe algorithm for computing minimum-volume enclosing ellipsoids." Optimization Methods & Software 23(1): 5-19. • Tutuncu, R. H., K. C. Toh, Michael Jeremy Todd. 2003, "Solving semidefinite-quadratic-linear programs using SDPT3." Mathematical Programming 95(2): 189-217. • Todd, Michael Jeremy. 2001, "Semidefinite Optimization." Acta Numerica 10: 515-560. • Nesterov, Y. E., Michael Jeremy Todd. 1997, "Self-scaled barriers and interior-point methods for convex programming." Mathematics of Operations Research 22(1): 1-42. • Todd, Michael Jeremy. 1986, "Polynomial Expected Behavior of a Pivoting Algorithm for Linear Complementarity and Linear-Programming Problems." Mathematical Programming 35(2): 173-192.

Selected Awards and Honors• College of Engineering Excellence in Teaching Awards (Cornell University) 2009 • Fellow (Society of Industrial and Applied Mathematics (SIAM)) 2009 • Fellow (Institute for Operations Research and the Management Sciences (INFORMS)) 2004 • John von Neumann Theory Prize (INFORMS) 2003 • George B. Dantzig Prize (Mathematical Programming Society (MPS) and SIAM) 1988

Huseyin Topaloglu

BiographyHuseyin Topaloglu is an Associate Professor in the School of Operations Research and Information En-gineering. He got his B.Sc. in Industrial Engineering from Bogazici University of Turkey and his Ph.D. in Operations Research and Financial Engineering from Princeton University. He has been a faculty member at the School of Operations Research and Information Engineering since 2002. Professor Topaloglu works on large-scale stochastic optimization problems that arise in areas such as revenue management, inventory con-trol, transportation logistics, and supply chain man-agement. He is an associate editor for the journals IIE Transactions, Mathematical Programming C, Opera-tions Research, and Transportation Science.

Research InterestsOne line of research pursued by Professor Topaloglu deals with operations management models that incor-porate customer choices. In many settings, including online retail, customers are offered a variety of choices among which they make a choice according to a choice model. In this case, the challenge is to come up with a way to model the choices of customers and to decide which assortment of products to offer to customers. Professor Topaloglu also works on large-scale airline network revenue management models that decide which itinerary products should be open to customers for sale as capacities on the flight network get depleted over time. He formulates these problems as large-scale stochastic optimization problems and seeks tractable solution methods. Another line of work focuses on ambulance redeployment problems that require dispatching ambulances to serve emergency calls in an effec-tive fashion. He views these problems as large-scale stochastic control problems and develops approximation methods.

Teaching InterestsProfessor Topaloglu has recently been teaching courses on simulation modeling, revenue management, and systems engineering. His simulation modeling course is devoted to how to model, simulate, and analyze complicated systems operating under uncertainty. Emphasis is on analysis of the data that are fed into the model, model building, and analysis of the model output. His revenue management course covers effective pricing, product offering, inventory control, and market segmentation strategies when demand for products occur randomly over time and one is forced to make the best use of limited and perishable product inven-tory. The ideas in this course find applications in airline pricing, hospitality, and online retail. His systems engineering course studies design and analysis of complex systems with the use of operations research tools.

Department: Operations Research and Information EngineeringTitle: Associate ProfessorAddress: 223 Frank H T Rhodes HallPhone: 607-255-0698email: ht88@cornell.eduWebsite: people.orie.cornell.edu/huseyin/

Continued next page

Service InterestsHuseyin Topaloglu serves as an associate editor for the journals IIE Transactions, Mathematical Program-ming C, Operations Research, and Transportation Science. He worked on organization committees for various conferences over the past year, including INFORMS Revenue Management and Pricing Section Conference, Production and Operations Management Conference, and the stochastic programming track of INFORMS Annual Meeting. He is the vice-chair for stochastic programming in INFORMS Optimization Soci-ety, and secretary and treasurer for INFORMS Revenue Management and Pricing Section. He is currently the chair of the INFORMS Transportation Science and Logistics Dissertation Award Committee. His service to Cornell includes working in various strategic planning, faculty recruiting, and curriculum committees, and serving as faculty advisor to Cornell Student Chapter of International Council on Systems Engineering.

Selected Publications• Erdelyi, Alexander, Huseyin Topaloglu. 2010"A Dynamic programming decomposition method for making overbooking decisions over an airline network." INFORMS Journal on Computing 22: 443-456. • Maxwell, Matthew, Mateo Restrepo, Shane G. Henderson, Huseyin Topaloglu. 2010"Approximate dynamic programming for ambulance redeployment." INFORMS Journal on Computing 22: 266-281. • Kunnumkal, Sumit, Huseyin Topaloglu. 2010"Computing time-dependent bid-prices in network revenue management problems." Transportation Science 44: 38-62. • Kunnumkal, Sumit, Huseyin Topaloglu. 2010"A new decomposition method for the network revenue management problem with customer choice behavior." Production and Operations Management 19: 575-590. • Rusmevichientong, Paat, C. Ding, Huseyin Topaloglu. 2011"Balancing Revenues and Repair Costs under Partial Information About Product Reliability." Manufacturing & Service Operations Management.

Selected Awards and Honors• INFORMS Revenue Management and Pricing Section Prize (INFORMS) 2010 • Outstanding Professor (ORIE Undergraduate Students) 2010 • COIN-OR Cup (INFORMS) 2009 • Professor of the Year (Master of Engineering Students, School of Operations Research and Information Engineering, Cornell University) 2006 • Sonny Yau `72 Excellence in Teaching (College of Engineering, Cornell University) 2005

Leslie Earl Trotter, Jr

BiographyLeslie Trotter received an A.B. (Mathematics) from Princeton University in 1965, an M.S. (Industrial and Systems Engineering) from Georgia Institute of Tech-nology in 1971, and a Ph.D. (Operations Research) from Cornell University in 1973. He had a postdoctoral appointment at the University of Wisconsin and was then on the faculty of Yale University before joining the Cornell faculty in 1975. He has held visiting appoint-ments at Bonn University, Germany (2 years); E.P.F. -- Lausanne, Switzerland (3 years); Augsburg Univer-sity, Germany (1 year); E.C. - Paris, France (1 year). His research is in the area of discrete optimization and he has published numerous research papers in this area. Professor Trotter was recipient of a Senior U.S. Scientist Award from the Humboldt Foundation and has been cited for the past 15 years in Who's Who in America. At Cornell he has received seven awards for teaching excellence and has directed the dissertation research of over 25 Ph.D. students; his research program has sponsored 10 postdoctoral students.

Research InterestsWithin the broad area of discrete and combinatorial optimization, Professor Trotter's research has focused on the following topics: structural and algorithmic properties of the stability number for simple undirected graphs, abstract duality models, computational implementation of and experimentation with parallel computing methods for integer programming, devel-opment and analysis of orthogonal projection algorithms for linear programming, and integer programming models for certain classical problems in number theory.

Teaching InterestsProfessor Trotter's teaching treats topics in the general field of optimization, primarily discrete and combina-torial optimization. His instruction emphasizes the fundamental interplay of operations research, mathemat-ics, and computer science in the context of strategic decision-making: development of models (operations research) motivated by real-world applications, of basic methodology (mathematics) designed for analysis of the models, and of algorithmic tools (computer science) whose implementation produces results required in the decision analysis.

Department: Operations Research and Information EngineeringTitle: ProfessorAddress: 235 Frank H T Rhodes HallPhone: 607-255-5360email: let3@cornell.eduWebsite: people.orie.cornell.edu/ltrotter/

Continued next page

Service InterestsProfessor Trotter currently serves are Associate Director (Undergraduate Studies) for the School of OR&IE; in the past he has served numerous times in this capacity, as well as in the positions of Director for the School and Director of Graduate Studies. His service contributions for the College of Engineering in recent years include chairing the International Programs Committee and serving on the Budget Advisory Task Force con-vened in response to the current economic crisis. At the University level, he served (and chaired) frequently on the Financial Policies Committee; it is noteworthy that his efforts on this committee (over the years) had significant impact on the University in the areas of faculty salary improvement and teaching responsibility.

Selected Publications• Amaldi, E., M. E. Pfetsch, Leslie Earl Trotter. 2003"On the maximum feasible subsystem problem, IISs and IIS-hypergraphs." Mathematical Programming 95(3): 533-554. • Trotter, Leslie Earl, L. Ladanyi, T Ralphs. 2001. "Branch, cut, and price: sequential and parallel". Computational Combinatorial Optimization. 223-260. • Sewell, E. C., Leslie Earl Trotter. 1995"Stability critical graphs and ranks facets of the stable set polytope." Discrete Mathematics 147(1-3): 247-255. • Carvalho, P. C. P., Leslie Earl Trotter. 1989"An Abstract Linear Duality Model." Mathematics of Operations Research 14(4): 639-663. • Domich, P. D., R. Kannan, Leslie Earl Trotter. 1987"Hermite Normal-Form Computation Using Modulo Determinant Arithmetic." Mathematics of Operations Research 12(1): 50-59.

Selected Awards and Honors• J.P. and Mary Barger Teaching Award (College of Engineering) 1998 • Who's Who in America Citation (Marquis) 1996 • Paramount Professor Award (College of Engineering) 1993 • Senior US Scientist Award (Alexander von Humboldt Foundation) 1987 • ORIE Undergraduate Teaching Excellence Award (Cornell, College of Engineering) 1977

Bruce William Turnbull

BiographyBruce Turnbull received the B.S. from Cambridge Uni-versity in 1967 and the Ph.D. from Cornell University in 1971 After serving on the faculty at Stanford Univer-sity and at the University of Oxford, he joined Cornell University in 1976, where he is currently Professor in the School of Operations Research and Information En-gineering where he previously served as Acting Direc-tor. From 2000--2002, he was founding Chairman of the newly formed Department of Statistical Science and currently also holds a professorial appointment there. In 1979 he was awarded the Snedecor Memorial Award by the American Statistical Association in recognition of his research. He has authored over 130 publications and is the co-author of a book on statistical procedures for monitoring clinical trials. He has been a consul-tant to many organizations, including the Oak Ridge National Laboratory, Institute for Energy Analysis; and various pharmaceutical companies. Turnbull has served on the Board of Directors of the National Insti-tute of Statistical Sciences, and on the Expert Review Panel for the National Toxicology Program Board of Scientific Counselors. He is on the Data and Safety Monitoring Committees for several major national and international clinical trials in the areas of cancer, heart disease, pulmonary disease and of AIDS sponsored by the National Institutes of Health and by the Veterans Administration. He has served on the editorial board of a number of statistical journals and is currently editor of the Chapman and Hall book series on biostatistics. He is a Fellow of the American Statistical Association and of the Royal Statistical Society.

Research InterestsAn attraction of working in the field of statistics is that it is eclectic. Professor Turnbull has worked in theory and methodology motivated by a wide variety of applications --- energy, and epidemiology; medicine and engineering; manufacturing and toxicology, etc. This is evidenced by the wide ranging topics in his list of publications. However, the major focus in the last few years has been on statistical design, monitoring and analysis of clinical trials. The recent emphasis has been on adaptive designs whereby changes in protocol (sample size, endpoint, patient population, dose level, etc.) can be modified in mid-course while still preserv-ing the prespecified statistical properties such as the false positive rate. Prof. Turnbull's particular interest is the tradeoff between the gains in flexibility of these methods compared with the loss of efficiency. Another active research project is the use of longitudinal biomarkers to identify and predict onset of disease --- e.g. PSA for prostate cancer in humans, ELISA scores for Johne's disease in dairy cattle.

Department: Operations Research and Information EngineeringTitle: ProfessorAddress: 227 Frank H T Rhodes HallPhone: 607-255-9131email: bwt2@cornell.eduWebsite: people.orie.cornell.edu/bruce/

Continued next page

Teaching InterestsProfessor Turnbull teaches courses on statistics --- theory, methodology and applications. This year he has taught ORIE6720 on sequential decision theory with particular applications both to manufacturing and to biomedical research. He also teaches a large sophomore class ENGRD2700 on "Basic Engineering Probability and Statistics". This too revolves around theory (commensurate with the students' mathematics prerequi-sites), methodology (e.g. decision-making under uncertainty, regression, experimental design, etc.) and ap-plications (quality assurance, process control, etc.) Above all however, the goal of Professor Turnbull in this course is to try to get the students to understand concepts of randomness and to "think statistically". Also , this semester is the first time that Professor Turnbull has incorporated iClickers to engage the students and to encourage their participation.

Service InterestsBruce Turnbull currently serves as a member of the professional accreditation committee for the American Statistical Association. In 2010, he had served on the initial committee that established the accreditation crite-ria and procedures for the "PStat" certification in 2010. He is Book Series Editor for the Chapman & Hall/CRC Biostatistics Series and previously been Associate Editor for Technometrics, American Statistician, Statistics in Medicine, Lifetime Data Analysis journals. He has served as Program Chair or on the organizing commit-tee for a number of conferences and workshops. He frequently gives invited talks and short courses at pro-fessional meetings. In 2011 these will include Third International Workshop on Sequential Methodologies at Stanford University; and the Biopharmaceutical Applied Statistics Symposium (Plenary speaker) to be held in Savannah, Georgia.

Selected Publications• Wang, C., Bruce William Turnbull, Y. T. Grohn, S. S. Nielsen. 2007"Nonparametric estimation of ROC curves based on Bayesian models when the true disease state is unknown." Journal of Agricultural Biological and Environmental Statistics 12(1): 128-146. • Turnbull, Bruce William. 2000.Group Sequential Methods with Applications to Clinical Trials. Chapman and Hall/CRC. • Turnbull, Bruce William, E. J. Iwano, W. S. Burnett, H. L. Howe, L. C. Clark. 1990"Monitoring for Clusters of Disease - Application to Leukemia Incidence in Upstate New-York." American Journal of Epidemiology 132(1): S136-S143. • Jennison, C., Bruce William Turnbull. 1989"Interim Analyses: the repeated confidence-interval approach." Journal of the Royal Statistical Society Series B-Methodological 51(3): 305-361. • Turnbull, Bruce William, T. J. Mitchell. 1978"Exploratory Analysis of Disease Prevalence Data from Survival-Sacrifice Experiments." Biometrics 34(4): 555-570.

Selected Awards and Honors• Accredited Professional Statistician (PStat, American Statistical Association) 2010 • Fellow (American Statistical Association) 1985 • George W. Snedecor Memorial Award for the best publication in Biometry for 1978 (American Statistical Association, Institute of Mathematical Statistics, Biometric Society) 1979

Martin T. Wells

BiographyMartin T. Wells, Ph.D., joined the Cornell faculty in 1987 and is the Charles A. Alexander Professor of Statistical Sciences, Professor and Chair of both the Department of Biological Statistics and Computational Biology and the Department of Statistical Sciences at Cornell University. He is also a Professor of Social Sta-tistics, Professor of Clinical Epidemiology and Health Services Research at Weill Medical School, an Elected Member of the Cornell Law School Faculty, as well as the Director of Research in the School of Industrial and Labor Relations. He teaches statistical methodology to undergraduate and graduate students in fields such as agriculture, biology, epidemiology, finance, law, medi-cine, nutrition, social science, and veterinary medicine as well as graduate courses in statistics. He has served on high-level national statistical committees, and has published many articles in leading statistical journals. His empirical legal studies have appeared in lead-ing legal publications, and cover civil rights, finance, punitive damages, judge and jury trials, and the death penalty. He is also the Editor in Chief of ASA-SIAM Series on Statistics and Applied Probability, Co-Editor of The Journal of Empirical Legal Studies, and served as the Editor of The Journal of the American Statistical Association-Reviews. He is a Fellow of the American Statistical Association and the Royal Statistical Society.

Research InterestMartin Wells' research interests center on applied and theoretical statistics and sometimes cross the bound-ary into applied probability. He has worked on inference questions in credit risk, economic damages, epide-miology, finance (physical and risk neutral worlds), graphical models, legal studies, microarrays, proteomics, quantitative trait loci, extremes, data networks and has considered estimation problems for heavy-tailed phenomena. His theoretical research has focused on Bayesian statistics, biostatistics, conditional inference, evidence assessment, functional data, hypothesis testing, saddlepoint approximations, and shrinkage estima-tion.

Department: Statistical SciencesTitle: Charles A. Alexander ProfessorAddress: 301 Malott HallPhone: 607-255-4388email: mtw1@cornell.eduWebsite: www.stat.cornell.edu/~wells/

David P. Williamson

BiographyDavid P. Williamson is a Professor at Cornell Universi-ty with a joint appointment in the School of Operations Research and Information Engineering and the Depart-ment of Information Science. He received his Ph.D. in Computer Science from MIT under Professor Michel X. Goemans in 1993. After a postdoc at Cornell under Professor Éva Tardos, he was a Research Staff Member for IBM Research at the T.J. Watson Research Center in Yorktown Heights, New York. From 2000 to 2003, he was the Senior Manager of the Computer Science Principles and Methodologies group at IBM's Almaden Research Center in San Jose, California. He moved to Cornell University in 2004.

His research focuses on finding efficient algorithms for hard discrete optimization problems, with a focus on approximation algorithms for problems in network de-sign, facility location, and scheduling. Other interests include algorithms for information networks.

Research InterestsProfessor Williamson works in the area of discrete optimization. In particular, he designs efficient heuris-tics with provable performance guarantees for NP-hard optimization problems; these heuristics are known as approximation algorithms. He has worked on approximation algorithms for a broad range of problems of interest in the operations research community, including network design, scheduling, facility location, clustering, ranking, and other related problems. Currently he is focusing his research efforts on the traveling salesman problem.

Teaching InterestsWilliamson's teaching time has been split between ORIE and Information Science. Within Information Sci-ence, Williamson has developed and taught a course on intermediate web programming and design (INFO 2300). The course introduces students with minimal programming experience to the web programming language PHP, and also introduces relational databases and the database language SQL in the context of de-signing web pages. Students must work on a number of individual projects (culminating in a project to write their own photo gallery site), then on a final team project in which the students design and code a site for an external client. Within Operations Research, Williamson has most recently taught graduate level courses in mathematical programming and optimization, including courses on the area of approximation algorithms, network flows, and the introductory course on mathematical programming required for all incoming ORIE graduate students.

Department: Operations Research and Information EngineeringTitle: ProfessorAddress: 236 Frank H T Rhodes HallPhone: 607 255-4883email: dw36@cornell.eduWebsite: www.davidpwilliamson.net/work

Continued next page

Service InterestsWilliamson has continued to serve as an associate editor for the journals ACM Transactions on Algorithms, SIAM Journal on Discrete Mathematics, and the SIAM Journal on Computing. He is also a member of the SIAM Journals Committee. He recently completed his fifth year as the Director of Undergraduate Studies for Information Science.

Selected Publications• Williamson, David P., David Shmoys. 2011. "The Design of Approximation Algorithms". 520. New York, NY:Cambridge University Press. • Williamson, David P., Guolong Lin, Chandrashekhar Nagarajan, Rajmohan Rajaraman. 2010"A General Approach for Incremental Approximation and Hierarchical Clustering." SIAM Journal on Computing 39: 3633-3669. • Williamson, David P., Anke van Zuylen. 2009"Deterministic Pivoting Algorithms for Constrained Ranking and Clustering Problems." Mathematics of Operations Research 34: 594-620. • Williamson, David P., Yogeshwer Sharma. 2009"Stackelberg Thresholds in Network Routing Games or the Value of Altruism." Games and Economic Behavior (67): 174-190. • Williamson, David P., Mateo Restrepo. 2009"A Simple GAP-Canceling Algorithm for the Generalized Maximum Flow Problem." Mathematical Programming (118): 47-74.

Selected Awards and Honors• Humboldt Research Award (Alexander von Humboldt Foundation) 2010 • Glover-Klingman Prize for the best 2009 Paper published in the journal Networks, co-authored with Eva Tardos (Networks) 2009 • Fulkerson Prize (Mathematical Programming Society) 2000 • 1999 SIAM Group on Optimization Prize (Society of Industrial and Applied Mathematics) 1996 • SIAM Richard C. Diprima Prize (Society of Industrial and Applied Mathematics) 1996

Dawn B. Woodard

BiographyDawn Woodard received her B.S. from Stanford Uni-versity, Palo Alto, CA, in 2001 and her Ph.D. in statis-tics from Duke University, Durham, NC, in 2007. She joined Cornell University in 2008, where she is cur-rently an Assistant Professor of Operations Research and Information Engineering. The focus of her research is on Bayesian statistics, both methodology and appli-cations, and on the convergence rates of Markov chain methods. She has authored or coauthored 9 refereed publications and 5 submitted publications in statistics, applied probability, and computer systems journals and books.

Research InterestsProfessor Woodard's work is on two closely related topics: (1) applied Bayesian statistics, primarily for management of operational systems; and (2) character-izing and reducing computational error in Bayesian statistics. To give examples of (1), she is working on statistics for management of distributed computing systems and Emergency Medical Services operations. Operations applications provide unique statistical chal-lenges due to their dynamical, high-dimensional, and nonlinear nature and the fact that statistical inference is often done within a decision optimization. Regard-ing topic (2), she is currently developing several approaches to characterizing and reducing the error associ-ated with the use of Markov chains. For example, one current focus is on characterizing the convergence rate of a Markov chain as a function of statistical quantities, such as the number of observations, parameters, or groups in the data.

Teaching InterestsProfessor Woodard has recently been teaching courses on data mining, statistical inference, and Monte Carlo methods. Her data mining course (4740) is on the use of statistical methods for achieving business goals, in particular using the very large datasets that are typical in modern commerce. Emphasis is on the process of building and interpreting various statistical models appropriate to such problems; the course uses a large number of case studies that build up to a major final project. Applications include sales prediction, credit risk evaluation, and targeted marketing. Her statistical principles course (6700) covers statistical decision theory and maximum likelihood, Bayesian, and best unbiased estimation, as well as hypothesis testing from both likelihood and Bayesian perspectives. The undergraduate probability and statistics course (2700) covers similar material at a more basic level, and additionally covers introductory probability. Her PhD topic course on Monte Carlo methods covers Monte Carlo and Markov chain Monte Carlo techniques for integration and counting problems arising in Bayesian statistics, statistical physics, and theoretical computer science.

Department: Operations Research and Information EngineeringTitle: Assistant ProfessorAddress: 228 Frank H T Rhodes Hallemail: dbw59@cornell.eduWebsite: people.orie.cornell.edu/woodard/

Continued next page

Service InterestsDawn Woodard frequently organizes and chairs sessions at statistics conferences including the Joint Sta-tistical meetings and the ENAR meeting of the International Biometric Society. She serves as a referee for a number of top statistics journals, including the Journal of the American Statistical Association, Biometrika, and the Journals of the Royal Statistical Society. She also develops and maintains publicly available S-PLUS software packages (implemented in C++) for using the methods published in her articles. She is a frequently requested public speaker.

Selected Publications• Woodard, Dawn B., M Goldszmidt. 2011"Online model-based clustering for crisis identification in distributed computing." Journal of the American Statistical Association. • Matteson, David, M W. McLean, Dawn B. Woodard, S G Henderson. 2011"Forcasting Emergency Medical Service Call Arrival Rates." Annals of Applied Statistics. • Woodard, Dawn B., R L. Wolpert, MA O'Connell. 2010"Spatial Inference of nitrate concentrations in groundwater." Journal of Agriculture, Biological, and Enviromental Statistics (15): 209-227. • Woodard, Dawn B., S. C. Schmidler, M. Huber. 2009"Sufficient Conditions for Torpid Mixing of Parallel and Simulated Tempering." Electronic Journal of Probability 14: 780-804. • Woodard, Dawn B., SC Schmidler, M Huber. 2009"Conditions for rapid mixing of parallel and simulated tempering on multimodal distributions." Annals of Applied Probability 19: 617-640.

Selected Awards and Honors• Best Poster Award (3rd International IMS/ISBA Joint Meeting) 2008 • Gertrude M. Cox Scholar (American Statistical Association) 2003 • James B. Duke Fellow (Duke University) 2002 • University Scholar (Duke University) 2002