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Operations Research Center Massachusetts Institute of Technology

GRADUATE STUDENT DIRECTORY

November 2018

Jonathan Z. Amar

Operations Research Center Massachusetts Institute of Technology 77 Massachusetts Avenue, E40-112 Cambridge, MA 02139 Email: [email protected]

24 Harold St #1 Somerville MA 02143

857-891-2137

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2020. GPA: 5.0/5.0 Research interests: Online Algorithms and Optimization Advisor: Prof. Nikolaos Trichakis Ecole Polytechnique, Palaiseau, France

MS & BS, June 2016. GPA 3.95/4.0 Applied Mathematics, Operations Research, Computer Science, Statistics. CPGE Lycée Massena, Nice, France Preparatory Prograam, 2013. Analysis, Algebra, Fundamental Physics

Work Experience 2018 Uber, San Francisco, CA (Summer) Data Science intern

Maketplace Optimization. Improved the matching algorithms using forecasts.

2015 Insensi Inc, New York, NY (Summer) Development intern

Designed a dashboard to track and visualize different company metrics. Research Experience 2016–Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Nikolaos Trichakis Online Optimization, Apprximation Algorithms, Optimization in Machine Learning.

2016-2016 Technion Israel Institue of Technology, Haifa, Israel

Research Intern Supervisor: Aaron Bental, Tamir Hazan Robust Optimmization in Machine Learning, data uncertainty and generalization.

2015-2016 Shortouch, Paris, France

Research Assistant Most relevant path in network of friends.

2014-2015 CMAP/Ecole Polytechnique, Paris, France Research Assistant Supervisor: Yassine Chitour Joint spectral radius estimation, numerical analysis.

2014-2014 Polestar/Ecole Polytechnique, Paris, France

Research Assistant Indoor localization, optimization of supply chain and order of stations.

Teaching Experience 2017 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Introductions to Operations Management (15.761)

Recitations, grading and office hours. 2014 Collège Stanislas, Paris, France (Fall) Teaching Assistant for Fundamental Physics

Preparation for national examination. Skills and Activities

Languages: English, French, Spanish, Hebrew Programming: Julia, Python, Matlab, R, C++

Citizenship Citizen of Canada and France

Lennart Baardman

MIT Operations Research Center 77 Massachusetts Avenue, E40-130 Cambridge, MA 02139 Email: [email protected]

617-417-7461 URL: http://www.mit.edu/~baardman/

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2019. GPA: 5.0/5.0 Track: Operations Management Advisor: Prof. Georgia Perakis

University of Cambridge, Cambridge, United Kingdom MASt in Mathematics, June 2014. Essay title: Applicable Combinatorial Auctions

University of Groningen, Groningen, Netherlands BSc in Econometrics and Operations Research, July 2013, summa cum laude. Thesis title: Multiple Traveling Salesman Problem with equal visits: An application to AS/RS scheduling Advisor: Prof. Kees Jan Roodbergen

Publications

Operationalizing Promotions for Retailers “Scheduling Promotion Vehicles to Boost Profits”, L. Baardman, M.C. Cohen, K. Panchamgam, G. Perakis, D. Segev, 2018, Management Science, published online April 2018 (with Oracle). First place in INFORMS Service Science Cluster Best Paper Award

“Data Analytics and Optimization to Improve Promotion Planning for Retailers”, L. Baardman, M.C. Cohen, J. Kalas, K. Panchamgam, G. Perakis, 2017, major revision in Production and Operations Management (with Oracle).

“Detecting Customer Trends for Optimal Promotion Targeting”, L. Baardman, S. Borjian Boroujeni, T. Cohen-Hillel, K. Panchamgam, G. Perakis, 2018, submitted to Manufacturing & Service Operations Management (with Oracle).

Learning Demand for New Products and Online Ads “Leveraging Comparables for New Product Sales Forecasting”, L. Baardman, I. Levin, G. Perakis, D. Singhvi, 2017, major revision in Operations Research (with Johnson & Johnson). First place in POMS Applied Research Challenge First place in POMS College of Supply Chain Management Best Student Paper Award Honorable mention in MIT Operations Research Center Best Student Paper Competition

“Learning Optimal Online Advertising Portfolios with Periodic Budgets”, L. Baardman, E. Fata, A. Pani, G. Perakis, 2018, submitted to Operations Research (with Adobe).

mailto:[email protected]

http://www.mit.edu/%7Ebaardman/

Finalist in George Nicholson Student Paper Competition (2018) “Dynamic Creative Content Optimization in Online Display Advertising”, L. Baardman, E. Fata, A. Pani, G. Perakis, work in progress (with Adobe). Business-to-Business Pricing for Manufacturers “Pass-through Constrained Vendor Funds for Promotion Planning”, L. Baardman, K. Panchamgam, G. Perakis, 2018, submitted to Manufacturing & Service Operations Management (with Oracle).

“Trade Funds from the Manufacturer’s Perspective: Joint Demand Forecasting and Dynamic Pricing”, L. Baardman, T. Cohen-Hillel, G. Perakis, work in progress (with CMPC).

Automated Ordering in Warehouses “Job Sequencing in a Miniload System”, L. Baardman, K.J. Roodbergen, H.J. Carlo, 2016, in 14th IMHRC Proceedings, Karlsruhe, Germany, 2016.

“A Special Case of the Multiple Traveling Salesman Problem in End-of-aisle Picking Systems”, L. Baardman, K.J. Roodbergen, H.J. Carlo, 2017, major revision in Transportation Science.

Presentations

“Scheduling Promotion Vehicles to Boost Profits”, L. Baardman, M.C. Cohen, K. Panchamgam, G. Perakis, D. Segev, presented at ISMP 2015, INFORMS 2015, POMS 2016, RMP 2016, MSOM 2016, INFORMS 2016.

“Pass-through Constrained Vendor Funds for Promotion Planning”, L. Baardman, K. Panchamgam, G. Perakis, presented at INFORMS 2016, MSOM 2017, INFORMS 2017.

“Leveraging Comparables for New Product Sales Forecasting”, L. Baardman, I. Levin, G. Perakis, D. Singhvi, presented at MSOM 2017, INFORMS 2017, ISB-POMS Workshop 2017, RMP 2018, MSOM Supply Chain Management SIG 2018, INFORMS Data Mining and Decision Analytics Workshop 2018.

“Customer-Trends for Personalized Demand Estimation and Targeted Promotions”, L. Baardman, S. Borjian Boroujeni, T. Cohen-Hillel, K. Panchamgam, G. Perakis, presented at MSOM 2017, INFORMS 2017, RMP 2018, MSOM 2018, INFORMS 2018.

“Online Advertising with Periodic Budgets”, L. Baardman, E. Fata, A. Pani, G. Perakis, presented at MSOM 2018, Young Researchers Workshop Cornell ORIE 2018, INFORMS 2018.

Patents

ORA170518-US-NP (O-441) - “Computer System and Method to Predict Customer Behavior Based on Inter-Customer Influences and to Control Distribution of Electronics Messages”, filed in Summer 2017 (L. Baardman, S. Borjian Boroujeni, T. Cohen-Hillel, K. Panchamgam, G. Perakis).

2018 Finalist in George Nicholson Student Paper Competition 2018 MIT Sloan Excellence in Teaching Award - Outstanding Teaching Assistant 2018 First place in POMS Applied Research Challenge 2018 First place in POMS College of Supply Chain Management Best Student Paper Award 2018 Honorable mention in MIT Operations Research Center Best Student Paper Competition 2016 First place in INFORMS Service Science Cluster Best Paper Award 2016 Finalist in Facebook Feppllowship 2015 Finalist in INFORMS Revenue Management and Pricing Practice Award 2013 Groningen University Fund-100 Prize 2011-2013 Member of the Honours College of the University of Groningen

Research Experience

2014–Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Prof. Georgia Perakis Conducting research into developing new demand and optimization models for advertising and promotion planning through both brick-and-mortar and online channels for retailers and manufacturers. Collaborations with Adobe, CMPC, Johnson & Johnson, Oracle.

2012-2013 University of Groningen, Groningen, Netherlands

Research Assistant Advisor: Prof. Kees Jan Roodbergen Conducted research on scheduling end-of-aisle picking systems, such as automated storage and retrieval systems (AS/RS).

Teaching Experience

2016-2018 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Data, Models, and Decisions – Executive MBA

Duties: assisting in developing lectures, teaching recitations, assisting students, writing and grading homework and exams. TA evaluation: 6.66/7 in 2016, 6.56/7 in 2017, 6.78/7 in 2018 Received MIT Sloan Excellence in Teaching Award - Outstanding Teaching Assistant – 2017-2018

2017 Massachusetts Institute of Technology, Cambridge, MA

Executive MBA Assistant for Global Organizations Lab Duties: assisting Executive MBA office with organizing the project teams for the Global Organizations Lab in the Action Learning Program.

2011-2013 University of Groningen, Groningen, Netherlands

Teaching Assistant for Mathematics I for EOR, Mathematics II for EOR, Multivariate Analysis, Sampling and Estimation, Hypothesis Testing, and Estimation and Testing Duties: teaching tutorials, assisting students, writing and grading assignments and exams.

Work Experience

2017 Adobe Systems Incorporated, San Jose, CA (Summer) Data Scientist Intern

Worked on developing adaptive robust learning algorithms for large-scale advertising portfolio optimization that advertisers use to determine bidding policies for online advertising.

2013 ABN AMRO Commercial Finance N.V., ‘s Hertogenbosch, Netherlands (Summer) Data Scientist Intern

Worked as the designer within the Business Intelligence project with the goal to use the data available to ABN AMRO Commercial Finance to identify new business opportunities. Wrote an R program generating statistical reports to enhance customer service.

Personal, Skills, and Activities

Citizenship: Netherlands Languages: Dutch (native), English (fluent), German (intermediate), Spanish (intermediate), French (basic) Programming Languages: Delphi, Gurobi, HTML/CSS, Java, Julia, JuMP, LaTeX, MATLAB, Oracle SQL, Python, R Software: AIMMS, Eviews, Microsoft Office, PlantSimulation, SPSS, Stata MIT Operations Research Center Seminar Student Coordinator (Fall 2016) MIT Operations Management Seminar Student Coordinator (Spring 2018) Reviewer for Operations Research and Naval Research Logistics

Citizenship Citizen of Netherlands

Lauren Berk


4 Charlesgate E Apt 706 Boston, MA 02215

908-947-8144

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, September 2019 GPA: 5.0/5.0 Advisor: Profs. Craig Carter and Robert Freund Yale University, New Haven, CT

BS in Intensive Mathematics, Summa Cum Laude, May 2012. GPA 3.95/4.0 Work Experience 2012-2014 Analytics Operations Engineering Inc., Boston, MA Analyst

Built a circulation optimizing and forecasting tool for the marketing team of a major retailer. Trained the client in the tool and the math necessary to use it, and assisted in the tool’s integration. Mined call center and repair data for a cell phone manufacturer to explain and mitigate abnormally high costs.

2011 Susquehanna International Group, Bala Cynwyd, PA (Summer) Researched the time decay of market straddle prices in Matlab and developed a corresponding

trading strategy. Wrote and refined existing trading and analysis algorithms as part of the automated trading group.

2010 Princeton Plasma Physics Lab, Princeton, NY (Summer) Summer Undergraduate Laboratory Internship

Short description of your position and what you worked on. 2009 National Security Agency, Ft. Meade, MD (Summer) Analyst

Analyzed large data sets using language modeling, probability analysis, and statistical algorithms. Produced a final product in Java with an intern team and co-authored a classified technical paper on our work. TS/Sensitive Compartmentalized Information/Special Intelligence.

Research Experience 2017–Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisors Profs. Craig Carter and Robert Freund: Studied the applications of operations research to educational technology through theory, simulation, and real-world experiments.

2014-2017 Massachusetts Institute of Technology, Cambridge, MA Research Assistant Advisor: Prof. Dimitris Bertsimas Studied applications of modern optimization to problems in statistics, including Sparse Principal Component Analysis. Assisted a consulting firm in Boston to forecast projects and revenue, and make more profitable hiring decisions.

Teaching Experience 2018 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for The Analytics Edge (15.071)

Served as a co-instructor for the course, developing and giving lectures along with Robert Friend. Supervised a team of 4 TAs. Developed new problem sets and programming tutorials.

2017 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for The Analytics Edge (15.071)

Revised lecture material and re-created recitation material for a run of 15.071 in Kuala Lumpur. 2017 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for The Analytics Edge (15.071) 2015 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Introduction to Mathematical Programming (15.081)

Wrote and led recitations, graded problem sets and exams, worked with the professor to develop assignments, provided office hours and assistance to students over email.

2010-2011 Yale University, New Haven, CT Teaching Assistant for Real Analysis (301) and Measure Theory (305)

Graded homework sets for undergraduate courses. Publications

”Prescriptive Analytics for Human Resource Planning in the Professional Services Industry”, with Dimitris Bertsimas, Alexander Weinstein, and Julia Yan, published in the European Journal of Operations Research, January 2019.

”Optimal Sparse Principal Component Analysis”, with Dimitris Bertsimas, under final review with Mathematical Programming Computation.

Honors and Awards 2018 Kaufman Teaching Certificate (Spring) Awarded for completing a semester-long training program in teaching at MIT. Skills and Activities

Programming: Julia, R, Python, SQL, VBA, Matlab, Mathematica, LaTeX Deacon of Old South Church 2013-2016

Treasurer of Old South Church 2016-2018

Citizenship Citizen of United States of America

Max Biggs


238 Prospect Street, Unit 2 Cambridge, MA, 02139

857-756-3914

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2019. GPA: 4.9/5.0 Advisor: Prof. Georgia Perakis University of Auckland, Auckland, NZ

BE(Hons), November, 2013. Thesis title: Mixed Integer Programming Formualtions for Diamond Cutting

Work Experience 2015 Amazon, Seattle, WA (Summer) Research Intern

Formulating and coding a large scale advertising optimization problem using mixed integer optization in Xpress.

2016 Thenamaris Shipping Company, Athens, Greece (Summer) Planning Consultant

Dynamic programming algorithms to design ship routes based on dynamic availability of cargoes.

2014 Harmonic Analytics Limited, Wellington, NZ Consulting Data Scientist Provided consulting services to help clients create value from their data using statistical and machine learning tools.

2013 Deloitte, Wellington, NZ (Summer) Consultant, Strategy and Operations

Worked on a RFP for a large public sector client. Research Experience 2014–Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Prof. Georgia Perakis Working on data-driven optimization, combining machine learning with operational optimization problems. Also working on dynamic routing with applications in maritime shipping and on-demand healthcare.

2012-2013 University of Auckland, Auckland, NZ

Summer research assistant Supervisor: Prof. Andrea Raith

Multi-objective optimization for bicycle routing Teaching Experience 2017 Massachusetts Institute of Technology, Cambridge, MA (Summer) Teaching Assistant for Operations Management (15.734)

This is a core class for Executive MBA students. My duties included teaching recitations online, grading coursework, holding office hours and responding to emails among others. I also developed recitation materials. For this course, I received an evaluation of 6.22/7.00.

2016 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Data Models and Decisions (15.730)

Similarly, my responsibilities included teaching recitations online, grading coursework, holding office hours and responding to emails among others. I also developed recitation materials and prepared assignments and exam questions. For this course, I received an evaluation of 6.63/7.00.

Publications

”Pricing for Heterogeneous Products: Analytics for Ticket Reslling”, with Alley, M., Hariss, R., Herrmann, C., Li, M., and Perakis, G. Submitted to MSOM, 2018.

”Optimizing Objective Functions Determined from Random Forests”, with Harris, R., and Perakis, G. Soon to be submitted. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2986630

”A Ranking Algorithm for Tramp Shipping in the Spot Market”, Perakis, G. In revision Management Science, 2017.

”Dynamic Routing Algorithms for OnDemand Healthcare”, with Perakis, G. Working paper.

Honors and Awards 2018 Data Mining Best Paper Finalist (Fall) “Optimizing Objective Functions Determined from Random Forests”

INFORMS 2017 Serivce Science Best Paper Finalist “A Ranking Algorithm for Tramp Shipping in the Spot Market”

INFORMS 2014 William Georgitti Fellowship Skills and Activities

Programming: Python, R, Julia, Matlab Optimization: Gurobi, Xpress, Ampl Coursework: Theory of Operations Management (both Inventory and Revenue Management), Integer Optimization, Robust Optimization, Machine Learning, Discrete Processes, Dynamic Programming and Stochastic Control, Fundamentals of Probability, Linear Programming.

Citizenship Citizen of New Zealand

Louis Chen


235 Albany Street Ashdown House #2012B

Cambridge, MA 02139 540-818-2166

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2019. GPA: 4.7/5.0 Advisor: Prof. David Simchi-Levi Rice University, Houston, TX

BA in Computational and Applied Mathematics, June 2012. Rice University, Houston, TX BS in Mechanical Engineering, June 2012.

Work Experience 2018 Alibaba, Bellevue, WA (June-Sept.) Summer Research Intern

Worked on analysis and design of cloud scheduling, as well as robust strategies for HEMA’s omni-channel inventory replenishment system Supervisor: Sen Yang

2017 Singapore University of Technology and Design, Singapore (June-Aug.) Visiting Research Scholar

Research work on Distributional Robust Linear/Discrete Optimization with Marginals Faculty Supervisor: Prof. Karthik Natarajan

2011 University of Southern California, Los Angeles, CA (June-Aug.) Summer Research Intern at CREATE (Center for Risk and Economic Analysis of Terrorism Events)

Worked on a warm-start implementation of a mixed-integer program solver for use in game-theoretic urban security algorithms.

Supervisors: Dr. Manish Jain and Prof. Milind Tambe 2010 Cornell University, Ithaca, NY (June-Aug.) NSF REU Summer Research Intern at CCMR(Cornell Center for Materials Research)

Studied osteoporosis effects on mechanical properties of bone, collected and analyzed nano-indentation data on bone samples of sheep treated with metabolic acidosis Supervisors: Dr. Jayme C. Burket and Professor Marjolein van der Meulen


Research Assistant Advisor: Prof. David Simchi-Levi

Distributionally Robust Optimization theory and applications in Operations Management problems like scheduling, network design, and inventory management.

Teaching Experience 2016 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Manufacturing Systems and Supply Chain Design, (15.763)

Responsible for recitation sessions and homework/report grading 2014 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Statistical Thinking and Data Analysis, (15.075)

Responsible for recitation sessions and homework/report grading 2014 Massachusetts Institute of Technology, Cambridge, MA (Summer) Teaching Assistant for Introduction to Operations Management, (15.761)

Responsible for recitation sessions and homework/report grading

Publications

”Distributionally Robust Linear and Discrete Optimization with Marginals”, with Will Ma, Karthik Natarajan, David Simchi-Levi, and Zhenzhen Yan, submitted to Operations Research, April, 2018.

”Distributionally Robust Max Flow with Marginals”, with Will Ma, James Orlin, and David Simchi-Levi, (to be submitted).

”Distributionally Robust Inventory Management of a Quick-Response Omni-Channel Fulfillment System”, with Hanzhang Qin, David Simchi-Levi, and Zirun Zhang, (in preparation).

”On the Structure of Cardinality Constrained Assortment Optimization”, with David Simchi-Levi (in preparation).

Honors and Awards 2011-2012 Scholarships: LJ Walsh, Chevron, Samuel T. Sikes Jr. 2010-2012 Department of Homeland Security Scholar 2008-2012 Rice University President’s Honor Roll 2004 World Chess Open (Philadelphia, PA) Under 1400 section, 22nd Place Skills and Activities

Computer Programming: C/C++, Java, Python, Julia, R, MATLAB, LATEX Citizenship Citizen of United States of America

Ryan Cory-Wright

Operations Research Center Massachusetts Institute of Technology 77 Massachusetts Avenue, E40-103 Cambridge, MA 02139 Website: ryancorywright.github.io

Email: [email protected] Cell: 617-955-5710

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2022. GPA: 5.0/5.0 Advisor: Prof. Dimitris Bertsimas University of Auckland, Auckland, New Zealand

BE (Hons) in Engineering Science, May 2017. GPA 8.84/9.00 Thesis title: Pricing wind under uncertainty Advisors: Andy Philpott and Golbon Zakeri Completed in three years via the accelerated pathway program; a highly intensive program which comprises direct entry to part II and three additional courses per year.

Publications “A scalable algorithm for sparse and robust portfolios”, with Dimitris Bertsimas, submitted to Operations Research, June 2018.

“Efficiency, savings, wealth transfers and risk-aversion in electricity markets with uncertain supply”, with Golbon Zakeri, working paper. ”Payment mechanisms for electricity markets with uncertain supply”, with Andy Philpott and Golbon Zakeri, Operations Research Letters. 46(1):116-121, 2018. https://doi.org/10.1016/j.orl.2017.11.017

Presentations “A scalable algorithm for sparse and robust portfolios”, with Dimitris Bertsimas, to be presented at INFORMS, November 2018.

“Payment mechanisms and risk-aversion in electricity markets with uncertain supply”, with Golbon Zakeri, presented at ISMP Bordeaux, July 2018. ”Stochastic Scheduling Pricing and Dispatch”, with Golbon Zakeri and Andy Philpott, presented at the EPOC mini workshop, July 2017.

”Cost-Recovering, Revenue-Adequate Single-Settlement Schemes for Electricity Markets”, with Andy Philpott and Golbon Zakeri, presented at ORSNZ, December 2016.

Honors and Awards 2017 Senior Scholar Award, University of Auckland For the highest GPA within graduating students in Engineering Science.

https://ryancorywright.github.io/

https://doi.org/10.1016/j.orl.2017.11.017

2016 ORSNZ Student Paper Competition, 1st Place “Cost-Recovering, Revenue-Adequate Single-Settlement Schemes for Electricity Markets”, with

Andy Philpott and Golbon Zakeri. For the best conference paper by a presenter within 5 years of graduation.

2014-2016 Deans Honours List x3, Faculty of Engineering, University of Auckland For earning a GPA within the top 5% of students in Engineering Science in a calendar year. 2014-2016 First in Course Award x5, University of Auckland For earning the highest mark in a course at the University of Auckland. 2013 NZQA Outstanding Scholar Award For placing in the top 50 students in the 2013 NZQA scholarship exams. Work and Research Experience 2017-Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Dimitris Bertsimas Developing high-quality interpretable solutions to problems which arise at the intersection of optimization and machine learning; for instance, sparsity-constrained optimization problems.

2016-2017 University of Auckland, Auckland, New Zealand Research Assistant Advisor: Golbon Zakeri

Developed methods for incorporating intermittent renewable energy into wholesale electricity markets via stochastic optimization. This comprised back-testing a stochastic dispatch mechanism on the New Zealand Electricity Market, extending the stochastic dispatch mechanism to incorporate risk-aversion, and measuring the impact of the dispatch mechanism on the aggregate system.

2014-2016 Derceto Ltd, Auckland, New Zealand Assistant Optimization Engineer

Assisted with installing a pump-scheduling optimization tool for two municipal water providers. Created a VBA/SQL tool to automate a 9-step process for updating historical demand curves.

Skills and Activities

Programming Languages: Julia, R, SQL, MATLAB, C++, HTML, CSS. Optimization Software: JuMP, AMPL, GAMS, Gurobi, CPLEX, MOSEK. Software: LaTeX, InDesign, Photoshop. Languages: English (native), French (conversational), German (beginner). Extracurriculars: Skiing, Running, Hiking, Water Polo.

Citizenship Citizen of New Zealand, Ireland

Andreea Georgescu


622 Boston Ave., Ste. 8E, Medford, MA, 02155

650-798-9043

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, May 2021. GPA: 5.0/5.0 Advisor: Profs. Retsef Levi, Vivek Farias Stanford University, Stanford, CA

BSc in Mathematics with Honors, June 2017. Thesis title: Representation Theory of the Symmetric Groups and Young Tableaux Mihai Viteazul National College, Bucharest, Romania High school diploma, June 2013. Romanian National Math Olympiad medalist, 2013 and 2012.

Work Experience 2016 Bridgewater Associates, Westport, CT (Summer) Investment Associate Summer Intern

Worked in the research departemnt, currency team.

2015 Nomis Solutions, San Bruno, CA (Summer) Business Analyst Summer Intern

Research and Development on the predictive model. Designed and tested algorithms to introduce a new feature in the model. Automatized code to fit the main pipeline (in Hive).

2012 Fair Isaac Corporation (FICO), San Jose, CA (Summer) Intern

Completed short readings and projects assigned by senior data scientist.


Research Assistant Advisors: Retsef Levi, Vivek Farias Investigating choice models not assuming IIA (independence of irrelevant alternatives). Working to leverage optimization methods to estimate traditional choice models.

2016-2017 Stanford University, Stanford, CA

Independent Researcher, Honors Thesis Supervisor: Daniel Bump Investigated new insights into combinatorial algorithms concerning Young tableaux by translating deep representation theoretical facts about the symmetric groups.


Programming Languages: Python, Julia, R, SQL/Hive Languages: Romanian (native), English (proficient), Russian, French (beginner) Athletic / Recreational: Rock climbing and Bouldering (advanced), Waltz, Tango (Intermediate)

Stanford Marketing, 2015-2016 Phi Beta Kappa, June 2017

Citizenship Citizen of Romania

Nicolas Guenon des Mesnards


143 Albany Street, apt 422 Cambridge, 02139

617-676 5499

Education Massachusetts Institute of Technology, Cambridge, MA

Candidate for SM in Operations Research; expected completion, June 2019. GPA: 5.0/5.0 Relevant coursework : Natural Language Processing, Computer Vision, Econometrics, Time Series analysis, Mathematics of Social Choice, Optimization Methods.

Advisor: Prof. Tauhid Zaman Ecole Centrale, Paris, France

Master of Engineering, expected completion, June 2019. Major: Applied Mathematics and Statistics Lycée Henri IV, Paris, France MPSI-MP*, Sept. 2012 - July 2014. Intensive preparation in Maths and Physics for the highly competitive national entrance exams to the leading French Grandes Écoles.

Work Experience 2017 BNP Paribas, London/Paris, UK/France (Fall/Spring) Quantitative Trading Researcher

Designed two alpha strategies on STOXX 600 as a member of the Automated Market Making research team. Modeled forward returns based on multi-objective genetic algorithms and CARTs on price dynamics instruments. Implemented and backtested the alphas in JAVA to further integrate these to AMM pipelines.


Research Assistant Advisor: Prof. Tauhid Zaman Detecting influence campaigns on social networks. Developed a bot detector that uncovers coordinated armies of bots, such as the ones that interfered with the 2016 US elections. Designed an algorithm that can find most likely bot/human labels as a min-cut in a graph, processing a joint probability over 100,000 users in under 10 minutes. Improved over state of the art bot detector botometer by 5% AUC on human labelled test sets, reaching less than 1% false positive at 80% true postitives rate: no humans are mistaken for bots. Took part in building and training a CNN to assess the political polarization of a tweet given its content, in order to further estimate the impact of bots on users polarities.

2016-2017 École Centrale Paris /MAS Laboratory, Paris, France

Undergraduate Researcher Supervisor: Frederic Abergel

Analyzed the origin of Stylized Facts observed on markets, from a behavioural finance perspective. Modeled the dynamics of stocks as an agent based system with herding behaviours. Built a python framework for simulating the evolution of stock prices, which revealed the existence of different volatility regimes.

Publications

”Detecting Influence Campaigns in Social Networks Using the Ising Model”, with Tauhid Zaman, https://arxiv.org/abs/1805.10244, last revised May, 2018.

”Koreans, Qanon, and Coordinated Bots”, Medium post, https://medium.com/mit-think-tank-on-the-complex-dynamics-of-2018/koreans-qanon-and-coordinated-bots-475f712b56b6, June, 2018.

Honors and Awards 2018 Best Student Paper in Social Media Analytics for the paper "Detecting Influence Campaigns in (Fall) Social Networks Using the Ising Model" INFORMS 2018 Nicolas Guenon des Mesnards and Tauhid Zaman, last revised May 2018,

(https://arxiv.org/abs/1805.10244) 2018 Jean Gaillard Memorial Fellowship (Fall) Committee on General Scholarships of Harvard University. Fellowship to study at the

Massachusetts Institute of Technology 2018 Press release - MIT Newsroom (Spring) “Detecting Influence Campaigns in Social Networks Using the Ising Model”

A new method for rooting out social media bots, By Dylan Walsh, July, 2018 (http://mitsloan.mit.edu/newsroom/articles/a-new-method-for-rooting-out-social-media-bots/)


Languages: English (Fluent), French (native), Spanish (intermediate) Programming: Python (expert), Pytorch/Keras (proficient), SQL (proficient), Unix (proficient), JAVA (prior experience), MPI (course experience), Matlab (course experience), R/stata (course experience) Sports: swimming at competitive level, mountain biking, trekking and running. Ran the Centrale Paris RAID, 250 km over 5 days. Central IV 2015, vice-president: organized an intervarsity english debating tournament gathering over 70 students from Europe and abroad.

Citizenship Citizen of France

Michael Hu


3611 Washington St., Unit B245 Jamaica Plain, MA, 02130

989-430-0750

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2019. Advisor: Prof. Retsef Levi University of Michigan, Ann Arbor, MI

BSE in Industrial and Operations Engineering, May 2014. Summa Cum Laude University of Michigan, Ann Arbor, MI B.S. in Pure Mathematics, May 2014. High Distinction

Work Experience 2012 Abbott Laboratories, Abbott Park, IL (May - Aug) Intern, Global Pharmaceutical Operations

Authored 3 standard operating procedures (SOPs) for OSIsoft PI software, which enabled the Engineering, Quality, and Operations divisions to electronically collect, manage, and analyze real-time data within manufacturing facilities while saving $14,000 annually by eliminating the usage of paper records. Won the national Abbott Intern Case Competition (400+ participants) by working in a team with 8 interns and presenting recommendations for the green and socially responsible implementation of a new manufacturing facility in Haiti.

2011 Toyota, Erlanger, KY (May - Aug) Co-op, Production Control - Project Planning and Management

Coordinated the timing and distribution of ~2 Engineering Change Instructions (ECIs) per day, thereby facilitating communication between designers/suppliers/manufacturers, and allowing for the rapid implementation of crucial adjustments in the production processes of 3 different automobile projects. Investigated 46 discrepancies in Toyota's Specification Management System (SMS), and created a document containing detailed countermeasures for each discrepancy; the discrepancies were rectified after the document was implemented by Toyota Motor Manufacturing Kentucky (TMMK), Toyota's largest manufacturing facility outside of Japan. Determined routing for 1004 parts with a 99.8% accuracy rate exceeding Toyota's target of 98.0%.

2010-2011 University of Michigan 3D Lab, Ann Arbor, MI Programmer

Extended an existing virtual reality (VR) interface in C++ to include functionality for Logitech G25 steering wheels. Integrated haptic feedback into VR simulations to achieve more immersive user experiences.


Research Assistant Advisor: Prof. Retsef Levi Creating and analyzing online scheduling algorithms that generalize online bin packing. Collaborating with a large academic medical center in several projects involving 1) evaluating physician work burden to redesign physician compensation schemes, 2) developing a new workflow for the management of hypertension patients, and 3) employing predictive analytics to reduce heart failure admissions.

2012-2014 University of Michigan, Ann Arbor, MI

Research Assistant Advisor: Mariel Lavieri Developed mathematical models to improve post-discharge checkup policies for patients in order to reduce hospital readmissions.

Teaching Experience 2017 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Introduction to Operations Management (15.761)

Teach recitations on operations management (topics include supply chain management, queueing, capacity analysis, revenue management, and pricing). Develop and grade homework assignments and case studies.

2016 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Healthcare Lab: Introduction to Healthcare Delivery in the US (15.777)

Teach remedial recitations on operations management, grade case studies and projects, develop syllabus, and coordinate lectures/lunches with c-level guest speakers.

2015 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Healthcare Lab: Introduction to Healthcare Delivery in the US

(15.767/15.777) Teach remedial recitations on operations management, grade case studies and projects, develop syllabus, and coordinate lectures/lunches with c-level guest speakers.

2011 University of Michigan, Ann Arbor, MI (Fall) Teaching Assistant for Engineers Making a Difference (ENGR 100)

Developed lesson plans for a 60-student first-year engineering course that stressed collaborative thinking, cultural awareness, and fundamental engineering processes. Served as an advisor for three 5-person engineering design teams by offering a 3rd party evaluation of their ideas and teamwork dynamics.

Publications

"Missed opportunities in preventing hospital readmissions: redesigning post-discharge checkup policies" X. Liu, M. Hu, J. Helm, M. Lavieri, T. Skolarus; Production and Operations Management, February 2018.

"A model to optimize followup care and reduce hospital readmissions after radical cystectomy", N. Krishnan, X. Liu, M. Hu, A. Helfand, B. Li, J. Helm, C. He, B. Hollenbeck, T. Skolarus, B. Jacobs, The Journal of Urology, May 2016.

"Understanding hospital readmission intensity after radical cystectomy", T. Skolarus, B. Jacobs, F. Schroeck, C. He, A. Helfand, J. Helm, M. Hu, M. Lavieri, B. Hollenbeck, The Journal of Urology, May 2015.

"Readmission intensity after high-risk surgery", B. Jacobs, C. He, B. Li, M. Hu, A. Helfand, N. Krishnan, B. Hollenbeck, J. Helm, M. Lavieri, T. Skolarus, The Journal of Urology, January 2015. "Sharpening the focus on causes and timing of readmission after radical cystectomy for bladder cancer", M. Hu, B. Jacobs, J. Montgomery, C. He, Z. Ye, Y. Zhang, T. Morgan, A. Weizer, K. Hafez, C. Lee, S. Gilbert, J. Brathwaite, M. Lavieri, J. Helm, B. Hollenbeck, T. Skolarus, Cancer, May 2014.

Refereed Conferences

"Measuring and predicting non-facetime work to inform physician compensation", M. Hu (presenter), R. Levi, S. Eisenstat, J. Doyle, K. Carlson, A. Huppert, MSOM Annual Conference, July 2018. "Valuing and optimizing non-facetime work in determining practice workload", M. Hu (presenter), S. Eisenstat, R. Levi, K. Carlson, J. Doyle, A. Huppert, SGIM Annual Meeting, April 2018. "Valuing and optimizing non-facetime work to inform physician compensation", K. Carlson, J. Doyle, S. Eisenstat, M. Hu (presenter), A. Huppert, R. Levi, INFORMS Annual Meeting, October 2017.

"Real-time outpatient scheduling algorithms", K. Ghobadi (presenter), M. Hu, R. Levi, A. Marshall, W. Rieb, B. Daily, I. Lennes, J. Stone, A. Zenteno., INFORMS Annual Meeting, October 2017. "Competitive analysis of online scheduling algorithms for infusion center appointments", K. Ghobadi, M. Hu (presenter), R. Levi, INFORMS Annual Meeting, November 2016.

"Understanding readmission intensity after cystectomy", T. Skolarus (presenter), H. Yeo, B. Jacobs, J. Montgomery, C. He, M. Hu, M. Lavieri, J. Helm, B. Hollenbeck, American Urological Association North Central Section 88th Annual Meeting, September 2014.

"Understanding readmissions after cystectomy", M. Hu (presenter), B. Jacobs, J. Montgomery, C. He, Z. Ye, J. Brathwaite, T. Morgan, K. Hafez, A. Weizer, S. Gilbert, C. Lee, M. Lavieri, J. Helm, B. Hollenbeck, T. Skolarus, American Urological Association North Central Section 87th Annual Meeting, October 2013.

Honors and Awards 2014 Outstanding Achievement in Mathematics University of Michigan Department of Mathematics 2014 Phi Beta Kappa, Phi Kappa Phi University of Michigan

2013 Healthcare Engineering and Patient Safety Travel Grant; $1,000 University of Michigan 2013 Clyde Johnson Scholarship; $10,000 University of Michigan Department of Industrial & Operations Engineering

Engineering scholarship awarded for academic accomplishments 2013 Accenture Industrial and Operations Engineering Scholarship; $2,500 Accenture, University of Michigan

Engineering scholarship awarded for academic and extracurricular accomplishments 2011 Holly and John Madigan Scholarship; $15,000 University of Michigan Ross School of Business

Business scholarship awarded for academic accomplishments 2011 BP Industry Scholarship; $10,000 BP, University of Michigan College of Engineering

Engineering scholarship awarded for academic and extracurricular accomplishments Skills and Activities

Programming: C/C++, Java, Julia, VB/VBA, MATLAB, SQL, Python, LaTeX Math/stats/simulation: R, SAS, Minitab, Mathematica, Maple, ProModel, Access, CPLEX, AMPL, Gurobi Director of Finance, InnoWorks (non-profit STEM camp), 2010-2014.

Associate Editor, Michigan Journal of Business, 2011-2013 Director of Advising, Society of Business Engineers, 2010-2012 Mentor, Big Brothers Big Sisters, 2008-2010

Citizenship Citizen of United States of America and Taiwan

Haihao (Sean) Lu


60 Wadsworth Street, Apt 14E Cambridge, MA, 02142

857-998-3092 web.mit.edu/haihao/www/

Education Massachusetts Institute of Technology, Cambridge, MA

Candidate for PhD dual in Mathematics and in Operations Research; expected completion, June 2019. GPA: 5.0 Thesis Title: Large-Scale Optimization Methods for Data-Science Applications

Advisor: Prof. Robert Freund Shanghai Jiao Tong University, Shanghai, China

B.S in Applied Mathematics, June 2014. Graduation with distinction Advisor: Prof. David Cai

Work Experience 2018 Google AI, Cambridge, MA (October) Student Researcher

Expanding the project on the huge-scale Linear Programming solver. Developing and implementing the Accelerated Gradient Boosting Machine for CART trees.

2018 Google AI, New York City, NY (Summer) Research Intern

Designed and implemented a huge-scale Linear Programming solver using first-order methods. The solver was able to solve a Linear Programming problem with multi- billion non-zeros on a single machine, and could be implemented distributedly across thousands of machines.

2017 Google Inc, New York City, NY (Summer) Software Engineer Intern

Developed new machine learning models for reserve price optimization of display ads (DRX), which gained a 2.7% revenue lift compared with the production model. The models were put on production in 2018Q2.

2016 IBM T.J. Watson Research Center, Yorktown Heights, NY (Summer) Research Intern

Developed new distributed optimization methods to solve deep learning problems, conducted extensive computational testing on preliminary tasks.

Teaching Experience 2017 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Computational Statistics (Undergraduate) and (18.S096) Curriculum design.

2016 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Optimization Methods (MBAn Core) and (15.093J/6.255J) Teaching recitations, assisting students, making, and grading homework and exams. 2016 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Nonlinear Optimization (PhD) and (15.084J/6.252J) Teaching recitations, assisting students, making and grading homework and exams. 2018 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for COURSE NAME and NUMBER

Mentor for MBAn student team Capstone Project with McKinsey & Company Publications

“Generalized Stochastic Frank-Wolfe Algorithm with Stochastic ‘Substitute’ Gradient for Structured Convex Optimization”, Haihao Lu and Robert M. Freund, submitted to Mathematical Programming, 2018.

“Approximate Leave-One-Out for High-Dimensional Non-Differentiable Learning Problems”, Shuaiwen Wang, Wenda Zhou, Arian Maleki, Haihao Lu and Vahab Mirrokni, submittedto Journal of Machine Learning Research, 2018. (A preliminary version was acceptedby ICML 2018.)

“Near-Optimal Online Knapsack Strategy for Real-Time Bidding in Internet Advertising”, Jonathan Amar, Nicholas Renegar and Haihao Lu, submitted to Management Science, 2018.

“New Computational Guarantees for Solving Convex Optimization Problems with First Order Methods, via a Function Growth Condition Measure”, Robert M. Freund, Haihao Lu, Mathematical Programming 2018, Vol.170, No.2: 445-477.

“Relatively-Smooth Convex Optimization by First-Order Methods, and Applications”, Haihao Lu, Robert M. Freund and Yurii Nesterov, SIAM Journal on Optimization, 2018, 28(1): 333-354.

“‘Relative-Continuity’ for Non-Lipschitz Non-Smooth Convex Optimization using Stochastic (or Deterministic) Mirror Descent”, Haihao Lu, to appear in INFORMS Journal on Optimization.

“Accelerating Greedy Coordinate Descent Methods”, Haihao Lu, Robert M. Freundand Vahab Mirrokni, ICML, 2018. “Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions”, Shuaiwen Wang, Wenda Zhou, Haihao Lu, Arian Maleki, Vahab Mirrokni, ICML, 2018. “Depth Creates No Bad Local Minima”, Haihao Lu and Kenji Kawaguchi, Technical Report. “Stochastic Linearization of β-Fermi-Pasta-Ulam Dynamics in Equilibrium and Nonequilibrium State”, Shi-xiao W. Jiang, Haihao Lu, Douglas Zhou, and David Cai, New Journal of Physics, 2016, 18(8): 083028. “Renormalized Dispersion Relations of β-Fermi-Pasta-Ulam Chains in Equilibrium and Nonequilibrium states”, Shi-xiao W. Jiang, Haihao Lu, Douglas Zhou, and David Cai. Physical Review E, 2014, 90(3): 032925.

Presentations and Posters Scalable Linear Programming via First-Order Methods

• Princeton Optimization Day (Poster), Princeton, NJ, September 2018 • Google Research, New York City, NY, August 2018 Generalized Stochastic Frank-Wolfe Algorithm with Stochastic ‘Substitute’ Gradient for Structured Convex Optimization • Columbia University, New York City, NY, August 2018 • International Symposium onMathematical Programming (ISMP), Bordeaux, France, July 2018 Accelerating Greedy Coordinate Descent Methods • Google Research, New York City, NY, July 2018 • International Conference on Machine Learning, Stockholm, Sweden, July 2018 • NYAS Meeting on Machine Learning (Poster), New York City, NY, March 2018 Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions • International Conference on Machine Learning (Poster), Stockholm, Sweden, July 2018 • NYAS Meeting on Machine Learning (Poster), New York City, NY, March 2018 Relative-Continuity for Non-Lipschitz Non-Smooth Convex Optimization using Stochastic (or Deterministic) Mirror Descent • INFORMS Meeting on Optimization, Denver, CO, March 2018 • INFORMS Annual Meeting, Houston, TX, Oct 2017 Relatively-Smooth Convex Optimization by First-Order Methods, and Applications • SIAM Conference on Optimization, Vancouver, Canada, May 2017 • INFORMS Annual Meeting, Nashville, TN, November 2016 Extending the Scope of Smooth and Non-Smooth Convex Optimization via First-Order Methods • University of Edinburgh, Edinburgh, UK, April 2016 Some New Results for Randomized Coordinate Gradient Descent • International Symposium on Mathematical Programming (ISMP), Pittsburg, PA, July 2015

Academic Service

Reviewer for Mathematical Programming, SIAM Journal on Optimization, Mathematics of Operations Research and Journal of Machine Learning Research. Session Chair for ISMP 2018. Session Chair for INFORMS Annual Meeting 2017. Session Chair for SIAM Conference on Optimization 2017.

Work in Progress “Randomized Gradient Boosting Machines”, Haihao Lu and Rahul Mazumder, to be

submitted to SIAM Journal on Optimization. “Accelerated Gradient Boosting Machines”, Haihao Lu, Sai Praneeth Reddy, Natalia Ponomareva and Vahab Mirrokni, in preparation. “Scalable Linear Programming via First-Order Methods”, Haihao Lu, Miles Lubin and David Applegate, in preparation. “qSGD: Ordered Empirical Risk Minimization”, Haihao Lu and Robert M. Freund, in preparation.


Computing: Python, Julia, MATLAB, R, SQL Language: English, Chinese Hobbies: Food/Cuisine, Kayaking, Sailing, Hiking, Skiing

Citizenship Citizen of China

Jing Lu


10 Centre St., Apt 4C, Cambridge, MA02139

646-639-5939

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2019. GPA: 5.0/5.0 Advisor: Prof. Carolina Osorio New York University, New York, NY

BS in Mathematics and Economics, June 2014. Work Experience 2018 GM Cruise LLC, San Francisco, CA (Summer) Operation Research & Data Scientist

• Improving the accuracy and precision of our Estimated Time of Arrival (ETAs) forecasts for picking up customers and dropping off customers using various machine learning models and various data sources. • Reviewing and improving the current pricing methodology while laying the groundwork for the next iteration of surge pricing while simultaneously repositioning vehicles.

2012 Joseph Investment, Beijing, China (Summer) Data Analyst

Collect data for all Chinese listed companies to study Chinese house and education market and participate in Taiqi Education's publication process


Research Assistant Advisor: Prof. Carolina Osorio • Working on using queueing theory to give a tractable and scalable approximation of traditional traffic flow theory, and use the scalable stochastic network model proposed to address traffic control problem on large-scale network both offline and online. • Working on smart sampling design for computationally costly stochastic traffic simulators, focus on the sampling strategies of simulation-based optimization.

2013 New York University, New York, NY

Optimizing Elevator Traffic Flow Supervisors: Dr. Lisa Rogers and Prof. Katie Newhall Optimized the elevator traffic in NYU's Courant Institution building by agent-based modeling, and gave some practical advices to passengers.

2013 New York University, New York, NY

Geometric Realization of Burnside Group B(3,3) Supervisor: Dr. Lukas Koehler

Studied combinatorial group theory and complex algebraic curves and investigated the topic with a view towards constructing a potential counterexample to Shafarevich conjecture.

2012 New York University, New York,NY

Tax Effect on Soda Consumption Supervisor: Prof. Andrew Paizis Studied the problem of how tax affects the consumption of junk food (soda), whether tax is an efficient method to control the consumption of junk food by implementing econometrical model.

Teaching Experience 2010-2014 New York University, New York, NY Teaching Assistant for Calculus I, II, III and Linear Algebra

Grading of homework sets for undergraduate courses. Publications and Talks

” Network loading model: a probabilistic, analytical, scalable and traffic-theoretic approach”, with Carolina Osorio, presented at the University of Hong Kong, the 7th international symposium on dynamic traffic assignment (DTA) “Smart Transportation” 2018. ” Network loading model: a probabilistic, analytical, scalable and traffic-theoretic approach”, with Carolina Osorio, submitted to Transportation Science, Aug 15th, 2018.

”A probabilistic traffic-theoretic network loading model suitable for large-scale network analysis”, with Carolina Osorio, accepted by Transportation Science, July 21st, 2017.

”On the approximation of joint queue-length distributions in large-scale urban networks”, with Carolina Osorio, submitted to ISTTT22, August, 2016.

“Analytical stochastic link transmission model suitable for large-scale analysis”, with Carolina Osorio, presented at ISMP 2015, INFORMS 2015.

“A probabilistic traffic theoretic and scalable network loading model”, with Carolina Osorio, presented at TU Delft, European Association for Research in Transportation (hEART) 2016.

Honors and Awards 2013 Honorable mention (Spring) “Mastering the Oven: a Genetic Approach”

Mathematical Contest in Modeling (MCM) 2013 2012 Honorable mention (Spring) “An Agent-Based Model for Camping Along the Big Long River”

Mathematical Contest in Modeling (MCM) 2012 2017-2018 CTL UPS Fellowships

This fellowship is a continuation of a program started in 1983, made possible by a grant to CTL from the UPS Foundation. It is designed to recognize and reward excellence and will be based solely on merit. (Center for Transportation & Logistics)


Languages: Chinese (native), English (fluent) Programming Languages: LaTeX, Matlab, R, Python, Java Software: Aimsun, Microsoft Office

Member of NYU Tae Kwon Do Club, 2010-2014 Research Fellow of Math Modeling Club of Courant Institute, 2011-2013 Member of MIT Sports Tae Kwon Do Club, 2015-2016


Sebastien Martin


238 Prospect St., Apt 2 Cambridge, 02139

(510) 229 2758

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2019. GPA: 5.0/5.0 Advisor: Profs. Dimitris Bertsimas and Patrick Jaillet École polytechnique, Palaiseau, France

MS in Applied Mathematics, June 2014. Multidisciplinary curriculum in Mathematics, Computer Science, Physics, Economy, Biology and Physics, followed by a specialization in Machine Learning, Probability, Statistics and Entrepreneurship. Lycée Louis-le-Grand, Paris, France Sept 2009, June 2011. Intensive preparation in Mathematics, Physics and Computer Science for the highly competitive national entrance exams to the French Grandes Écoles.

Work Experience 2017-18 Boston Public Schools, Boston, MA Research Partner

Worked with Boston Public Schools to design an algorithm to route their fleet of >800 school buses, together with D. Bertsimas and A. Delarue.We currently route 30,000 BPS students to their school for the 2017-2018 school year, saving $5M per year in transportation costs, that are re-invested in the classrooms. We are also working with them on changing the bell times of 200 schools to further optimize the bus routes, a project that combines the challenges of large-scale optimization and public policy. This collaboration has been featured in the Wall Street Journal and the Boston Globe.

2016 Google, Mountain View, CA (Summer) Software Engineering Intern

Successfully passed the Google Software Engineer coding interviews.Worked for Google Maps. Researched, experimented and implemented novel algorithms to improve maps and navigation data using large geolocation datasets (> 100Gb).

2013 Startup “Sam”, Palaiseau, France Founder

Designed and built a smart bicycle that automatically shifts gears, using machine learning to learn the behavior of experienced cyclists. I partnered with Decathlon, the European main sports gear retailer.

2011-12 French Army Firefighter Officer

Ecole polytechnique (a military university) required me to do one year of military service, to learn about leadership and decision making. I served as the leader of a platoon of 30 military firefighters.


Research Assistant Advisor: Dimitris Bertsimas and Patrick Jaillet My research is in the areas of optimization and machine learning, with applications in transportation and public policy. My current focus is to scale traditional optimization and machine learning algorithms to real world problems involving large datasets. I have the pleasure to partner with Boston Public School to optimize their bus routes and school start times.

2014 University of California, Berkeley , Berkeley, CA

Visiting Researcher Supervisor: Alexandre Bayen Studied the potential impact of large scale cyber-attacks on transportation networks (freeways). This worked mixed freeway flow control, cyber security, multi-objective optimization and visualizations.

Teaching Experience 2018 Massachusetts Institute of Technology, Cambridge, MA (April) Teaching Assistant for The Analytics Edge, (15.071)

Guest lecturer (NOT TA) I gave the lecture: Driving Policy with Optimization, using my research as an example of prescriptive analytics for MBA students.

2017 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Introduction to Probability, (6.041)

112 students. Organized 3 weekly tutorials, and full-class exam reviews. 2016 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for The Analytics Edge, (15.071)

Weekly Recitations for ~80 MBA students, introducing new material not covered in lectures. Management of team projects.

Publications

”From School Buses to Start Times: Driving Policy with Optimization”, with D. Bertsimas, A. Delarue, and P. Jaillet, second round of revisions, PNAS.

”Travel Time Estimation in the Age of Big Data”, with D. Bertsimas, A. Delarue, and P. Jaillet, to appear in Operations Research, 2018.

”Online Vehicle Routing: the Edge of Optimization in Large-Scale Applications”, with D. Bertsimas and P. Jaillet, to appear in Operations Research, 2018.

”Creating complex congestion patterns via multi-objective optimal freeway traffic control with application to cyber-security”, with J. Reilly, M. Payer, and A. Bayen, Transportation Research Part B, 91, 366-382 (2016).

Honors and Awards 2018 Doing Good with Good OR paper competition (Fall) "From School Buses to Start Times: Driving Policy with Optimization”

Finalist of this paper competition of the INFORMS 2018 annual meeting. The recipients will be disclosed during the conference.

2018 Best Student Paper, MIT Operations Research Center "From School Buses to Start Times: Driving Policy with Optimization

Description of award and related paper etc. (Organization or Conference) 2018 MIT Policy Hackathon "Future of Work" winning team (Spring) "Shared Responsibility: Social Forces in Response to Market Failures"

Description of award and related paper etc. (Organization or Conference) 2018 Best Presentation, MIT LIDS Student Conference (Winter) "Online Vehicle Routing: the Edge of Optimization in Large-Scale Applications"

Voted best presentation out of 22 PhD students presentations. 2017 Boston Public Schools Transportation Challenge Winner (Summer) Winner (with D. Bertsimas and A. Delarue) of a $30,000 competition to optimize school bus

routes. This competition was the beginning of my partnership with Boston Public Schools.

2013 Zodiac Aerospace - Gerondeau Innovation Prize Won a €10,000 prize for most innovative start-up, using machine learning to build a smart bicycle

that automatically shifts gears. 2012 French Medal of National Defense, Bronze level I received the French military honor for my cumulated time in external operations during my

year of service as a military firefighter. Skills and Activities

Computer skills: Julia, Java, Python, SQL, R, MapReduce Extra-curricular activities: General aviation pilot, long distance runner and pianist. Languages: French (native), English (fluent), Spanish (intermediate) Member of ORC REFS team (Resources for Easing Friction and Stress): Support students that face issues related to research, communicaiton and personal matters. I am trained in conflict management and mediation for this purpose.

Citizenship Citizen of France

Nishanth Mundru

Operations Research Center Massachusetts Institute of Technology 77 Massachusetts Avenue, E40-103 Cambridge, MA 02139 URL: https://nmundru.github.io/

Email: [email protected] 70 Pacific St,

Cambridge, MA 02139 617-682-9824

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for Ph.D. in Operations Research; expected completion, June 2019. GPA: 4.9/5.0 Academic distinctions, i.e., magna cum laude Advisor: Prof. Dimitris Bertsimas Indian Institute of Technology, Bombay, India

BTech in Chemical Engineering with a Minor in Applied Statistics, July 2012. Work Experience 2016 Google Research, New York City, NY (Summer) Quantitative Analyst Intern

Worked on rank aggregation problems, part of a tool being developed at Google. Formulated it as a matrix completion problem with additional constraints, and adapted existing iterative algorithms for this problem. Our results outperformed the existing baseline method.

2012-2013 WorldQuant Research, LLC, Mumbai, India Quantitative Researcher

Creating and validating data driven predictive and original quantitative algorithms for trading various financial instruments - US Equities and futures.


Research Assistant Advisor: Prof. Dimitris Bertsimas My current focus is on prescriptive analytics - developing methods that prescribe high quality decisions directly from data. I aspire to conduct research that focuses on arriving at decisions directly starting from data. I utilize tools and techniques from machine learning (ML), optimization, and statistics for formulating these problems, obtaining insights and understanding the computational behavior of these algorithms. I have also worked on machine learning algorithms from an optimization lens, and real world applications in transportation.

Teaching Experience 2018 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Introduction to Operations Management, 15.761 (MBA) Conducted weekly recitations, held weekly office hours, graded case studies and home work. 2017 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Optimization methods for Business Analytics, 15.053 (Undergraduate)

Conducted weekly recitations, held weekly office hours, (co) created and graded midterms. 2016 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Analytics Edge, 15.071 (MBA)

Conducted weekly recitations, held office hours, graded problem sets and the final project. 2015 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Robust Modeling, Optimization and Computation, 15.094 (Ph.D.)

Co-created and graded problem sets and the midterm, conducted weekly recitations, and held office hours.

Publications

”Optimal Prescriptive Trees”, with D. Bertsimas, and J. Dunn, INFORMS Journal on Optimization, 2018, to appear. ”The Airlift Planning Problem”, with D. Bertsimas, A. Chang, and V.V. Misic, Transportation Science, 2018, to appear. ”Computation of Alarm Relevant Probabilities using Geometric Modeling”, with R. Ghosh, and M. Bhushan, IFAC-Papers Online, 50(1), 2866-2871.

Working Papers

”Sparse Convex Regression", with D. Bertsimas, submitted to INFORMS Journal of Computing, 2017, Minor revision.

”Prescriptive Analytics for Observational Data”, with D. Bertsimas, and C. McCord, working paper, 2018. ”The Robust Airlift Planning Problem", with D. Bertsimas, A. Chang, and V. Misic, working paper, 2018.


Languages: English, Telugu, Hindi. Computing: Julia, R, MATLAB, C++, Python, MySQL. Coursework: Optimization (Linear, Integer, Robust), Statistical Learning Theory, Probability Theory, Analytics Edge, Machine Learning for Healthcare.

Citizenship Citizen of India

Colin Pawlowski

Operations Research Center Massachusetts Institute of Technology 77 Massachusetts Avenue, E40-130 Cambridge, MA 02139-4307 Email: [email protected]

318 Beacon St, Apt. 3 Somerville, MA 02143

910-617-9317

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2019. GPA: 5.0/5.0 Supported by National Science Foundation (NSF) Graduate Research Fellowship.

Advisor: Prof Dimitris Bertsimas Yale University, New Haven, CT

BS in Mathematics (Intensive), May 2014. GPA: 3.93/4.0 Magna Cum Laude, Phi Beta Kappa Society.

Work Experience 2017 Wealthfront, Redwood City, CA (Summer) Research Intern

Built a research platform to evaluate financial planning strategies for retirement for an automated investment services firm.

2014 Ancera, Inc., Branford, CT (Summer) Analytics Intern

Brainstormed and strategized data approaches for biotech startup specializing in rapid microbial testing for food producers.


Research Assistant Advisor: Prof. Dimitris Bertsimas Developed fast, tractable algorithms in machine learning for statistical inference using tools from optimization, with a focus on SVMs for classification, k-means clustering, and missing data imputation.

2013 Mount Holyoke College REU, South Hadley, MA (Summer) Undergraduate Researcher Advisor: Prof. Dylan Shepardson

Researched mathematical modeling and epidemiology. Programmed a population-level model for tuberculosis in the USA, with cost analysis for several intervention strategies.

2011-2012 NASA Flight Opportunities Program, Houston, TX Microgravity Research Team Leader Advisor: Andrew Szymkowiak Led a team of six students; built a prototype of a 3-D cell culture apparatus and tested it aboard NASA’s zero-gravity plane.

Teaching Experience 2017 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for MBA course: The Analytics Edge (15.071)

Taught weekly recitations in the R programming language, developed and graded assignments, met with student groups to hone final project ideas.

2015 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for MBA core course: Data, Models, and Decisions (15.060)

Taught weekly recitations, developed course materials and exams, worked one-on-one with students, graded assignments.

Publications

“From Predictive Methods to Missing Data Imputation: An Optimization Approach”, with D. Bertsimas and Y. Zhuo; submitted to Journal of Machine Learning Research, 2017. “Robust Classification”, with D. Bertsimas, J. Dunn, and Y. Zhuo; submitted to INFORMS Journal on Optimization, 2017.

Honors and Awards 2016 athenahealth Hackathon Grand Prize 2015 NSF Graduate Fellowship 2012 Richter Summer Fellowship 2011 NASA Flight Opportunities Program, national research grant 2011 Connecticut Space Grant Consortium Project Grant Skills and Activities Programming: Java, Python, Julia

Mathematical Tools: Matlab, R Volunteer, The Full Belly Project, Non-profit engineering group, 2010-2012


Nicholas Renegar


225 Chestnut St. Apt. 6 Cambridge, MA 02139

206-518-0193

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, May 2021. GPA: 5.0/5.0 Advisor: Prof. Retsef Levi Cornell University, Ithaca, NY

BSc, Operations Research & BA, Mathematics, May 2010. Work Experience 2010-2015 Milliman, Inc., Seattle, WA (Semester) Healthcare Consulting Actuarial Analyst

Developed commercial software to price claims to Medicare fee schedule, built funding models for WA state healthcare exchange, created proprietary risk score models and other funding model peices for Department of Veterans Affairs, research on the impact of the ACA.

2008 Solamere Capital, New York, NY (Summer) Private Equity Intern

Created methods of identifying private companies for investment through use of technology, and developed LBO models.


Research Assistant Advisor: Retsef Levi Supply chain analytics, optimization, food safety, healthcare, and internet advertising.

Teaching Experience 2018 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Healthcare Lab: Intro to Healthcare Delivery in the US (15.777)

Teaching Background Seminars, Assisting Students on Action-Learning Projects, Grading 2018 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Introduction to Operations Management (15.761)

Teaching Weekly Seminars, Running Simulation-Based Projects, Grading 2010 Cornell University, Ithaca, NY (Spring) Teaching Assistant for Introduction to Game Theory (ORIE 4350)

Teaching Weekly Seminars, Grading

Publications

”Near-Optimal Online Knapsack Strategy for Real-Time Bidding in Internet Advertising”, with Jon Amar and Haihao Lu, and, submitted to Management Science, October, 2018.

”Network Based Risk Analytics in Global Food Supply Chains”, with Retsef Levi and Tauhid Zaman. Working Paper.

”Automated Big Data Consolidation for Food Safety Policy in China”, with Retsef Levi. Working Paper.

”Risk Analysis on Aquatic Products in China: Adulterants and Traceability”, with Retsef Levi, Jiehong Zhou, Cangyu Jin, Weihua Zhou, and Qiao Liang. Working Paper.


Programming: Python, R, SAS, C#, JAVA, SQL, VBA, Julia Citizenship Citizen of the United States of America

Fransisca Susan


70 Pacific Street Cambridge, MA

617-583-3599

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, 2023. GPA: 5.0/5.0 Advisor: Prof. Andrew Lo Massachusetts Institute of Technology, Cambridge, MA

BS in Mathematics and Computer Science, minor in Economics, June 2018. GPA: 5.0/5.0 Work Experience 2018 Goldman Sachs, New York, NY (Summer) Securities Division Summer Strategist

Ten-week rotational internship program involving five-week segments with two teams, automated the sector hedge fund VIP custom basket automation

2017 Goldman Sachs, New York, NY (Summer) Securities Summer Analyst

Short description of your position and what you worked on.

2017 Traveloka, Jakarta, Indonesia (Winter) Data Scientist

Developed a recommendation system algorithm for the hotel business using various machine learning and statistics approach.

2016 Twitter, Inc., San Franciscso, CA (Summer) Software Engineering Intern

Conducted feature experiments on who to follow modules for new users and resurrected users, created web reonboarding feature, a flow to refine social graph of resurrected users, implemented IOS feature for Datalytics, a hack week project to measure the amount of data usage spent on Twitter application.


Research Assistant Advisor: Professor Andrew Lo Currently working on developing multi-party computation algorithm to share secretive financial data securely across companies; and stochastic portfolio optimization for taxes-related securities.

2017-2018 Massachusetts Institute of Technology, Cambridge, MA

Undergraduate Research Assistant Supervisor: Professor James Glass, Yonatan Belinkov

Developed a classifier to investigate how well Neural Machine Translation model infers multiple senses from homonyms, investigated the effects of the different layers, target languages, and model architecture on word disambiguation ability

2015 Massachusetts Institute of Technology, Cambridge, MA

Undergraduate Research Assistant Supervisor: Professor Jack Dennis Implemented parallel BFS Algorithm on Fresh Breeze Machine, a new multiprocessor chip architecture, built a benchmark for testing codes on Fresh Breeze Machine as a multi-core system.

Teaching Experience 2018 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Introduction to Machine Learning, 6.036/6.862

Duties: holding office hours, making and grading homeworks and exams Honors and Awards 2017 William Lowell Putnam Mathematical Competition Honorable Mention 2012-2014 International Mathematics Olympiad 1 Silver, 2 Bronze Medals

2014-2018 Presidential Scholarship Skills and Activities

Languages: Indonesian (native), English, Malay, Chinese (basic) Programming: Python, Julia, Gurobi, Java, Scala, C++, Javascript, HTML, CSS Association of Indonesian Student in New England, President

Citizenship Citizen of Indonesia

Li Wang


60 Wadsworth St 7E Cambridge, MA 02142

607-379-5636

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2020. GPA: 5.0/5.0 Advisor: Prof. David Simchi-Levi Cornell University, Ithaca, NY

BS in Operations Research and Computer Science, May 2015. Thesis title: The Topology of Overlapping Portfolio Networks

Work Experience 2018 Alibaba Group, Bellevue, WA (Summer) Research Intern

Worked on online learning algorithms for large-scale product selection problems. Research Experience 2015–Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Prof. David Simchi-Levi Supply chain analytics in collaboration with a high-tech company. Data-driven revenue management research.

2014-2015 Cornell University, Ithaca, NY

Research Assistant Supervisor: Prof. Peter Frazier Statistical prediction of the stability of small interfering RNA.

2013-2015 Cornell University , Ithaca, NY

Research Assistant Supervisor: Prof. Andreea Minca Network analysis of portfolio defaults in the financial network.

Teaching Experience 2017 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Supply Chain Planning (15.762J/ESD.267J/1.273J)

Led weekly recitations of 90 students. Graded cases. 2017 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for Manufacturing System and Supply Chain Design (15.763J/ESD.268J/1.274J)

Led weekly recitations of 50 students. Graded cases.

2014 Cornell University, Ithaca, NY (Spring) Teaching Assistant for Industrial Data and Systems Analysis (ORIE 3120)

Led weekly recitations of 50 students and graded homework and exams. Helped design exams and grading rubrics.

Publications

”The Topology of Overlapping Portfolio Networks”, with W. Guo and A. Minca, published on Statistics & Risk Modeling, December, 2016.

Honors and Awards 2015 Merrill Presidential Scholar (Spring) The highest honor given to a graduating senior student. (Cornell University) 2015 Cornell University Class of 2015 College Banner Bearer (Spring) Top 5 GPA among 800 students in College of Engineering. (Cornell University) 2015 Byron W. Saunders Award (Spring) Best academic performance in Operations Research. (Cornell University) Citizenship Citizen of People’s Republic of China

Yuchen Wang


100 Memorial Drive Cambridge, 02142

617-676-8855

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2020. GPA: 5.0/5.0 Advisor: Prof. Dimitris Bertsimas

Peking University, Beijing, China BS in Mathematics and Economics, June 2016. Summa Cum Laude.

Work Experience 2018 TheOfficialBoard, France Research Assistant

Trained a Recurrent Neural Network (RNN) model to predict the department of people based on his job title, used Global Vectors for Word Representation (GloVe) to make recommendations of short titles based on their job titles.

2017 ISNetworld, USA Research Assistant

Used advanced machine learning method to develop a recommendation system for the client.

2016 Estrategia, Peru Research Assistant

Helped the largest family fund of Peru to build a portfolio management model and implemented time-varying linear regression method for predictions.


Research Assistant Advisor: Dimitris Bertsimas My primary research interest is the intersection of modern optimization and machine learning with application in healthcare. We are currently working on the algorithm about developing Optimal Nonlinear Trees. We use global optimization solution to replace the original greedy method when building decision trees in order to increase the accuracy of the whole model. Using the tool that we developed, we improve the prediction rules of children after head trauma who need computed tomography (CT). We also propose a new rule for liver allocation using the advanced machine learning tools we developed.

2014-2015 Peking University, Beijing, China

Research Assistant Supervisor: Lan Wu

Used the knowledge of nonsynchronous trading to find the influence of T+1 mechanism in Chinese stock market.

Teaching Experience 2017 Massachusetts Institute of Technology, Cambridge, MA (Spring) Teaching Assistant for The Analytics Capstone(15.089)

Mentored four Masters of Business Analytics(MBAn) Student to do two projects with McKinsey & Company. The first topic is spatiotemporal analysis of industrial agglomeration. The second topic is extract named topics from unlabeled test.

2016 MIT edx.org, Cambridge, MA (Spring) Teaching Assistant for The Analytics Edge(15.071x)

Hosted online forum and answered questions. 2018 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for 15.095: Machine Learning Under a Modern Optimization Lens

Conducted weekly recitations about machine learning and optimization for 60 students, created and graded 6 problem sets and midterms. Graded final project.

Publications

”Improved triaging of diagnostic computed tomography for children after head trauma”, with D. Bertsimas, J. Dunn and T. Trikalinos, submitted, Month, Year.

”Optimized prediction of mortality(OPOM): a novel machine-learning approach to prioritize liver transplant candidate”, with D. Bertsimas, J. Kung, N. Trichakis, P. Vagefi, R.Hirose.

” Optimal Nonlinear Trees for Predictions”, with D. Bertsimas and J. Dunn, working paper.

” Optimal District for Liver Transplantation”, D. Bertsimas, T. Papalexopoulos, N. Trichakis and P. Vagefi, working paper.

Honors and Awards 2016 Outstanding Graduate Award, Peking University 2015 Canon Scholarship, Peking University 2014 Champion of KPMG Accounting Case Competition 2013 May Fourth Scholarship, Peking University 2012 Gold Medal in 2012 Chinese Mathematical Olympiad(CMO), China Skills and Activities

Programming: Python,Julia,C/C++,Matlab,R Optimization/Machine learning: Gurobi ,Tensorflow, Pytorch, Sklearn Interests: Go(5 Duan),Swimming,Table Tennis


Julia Yan


10 Stanford Terrace, Unit 1 Somerville, MA 02143

609-947-3947

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2020. GPA: 5.0/5.0 Advisor: Prof. Dimitris Bertsimas Princeton University, Princeton, NJ

AB summa cum laude in Chemistry and Applications of Computing, June 2013. GPA: 3.9/4.0 Thesis title: Control Landscape Topology for Nonlinear Quantum Dynamics

Work Experience 2013-15 Analytics Operations Engineering, Boston, MA Analyst

Projects included: designing and implementing algorithms to redistribute inventory between distribution centers of a major fashion retailer, developing a large-scale scheduling algorithm for a national sports league, optimizing pricing and discounting for an online fast-fashion retailer

2012 J.P. Morgan, New York City, NY Investment Banking Analyst, Diversified Industries Research Experience 2015–Present Massachusetts Institute of Technology, Cambridge, MA

Research Assistant Advisor: Prof. Dimitris Bertsimas Developing scalable optimization algorithms for network design, scheduling, pricing, and demand estimation in a public transportation setting.

2011-2013 Princeton University, Princeton, NJ

Undergraduate Research Assistant Supervisor: Prof. Herschel Rabitz

Teaching Experience 2018 edX, Cambridge, MA Teaching Assistant for The Analytics Edge (15.071x) 2018 Massachusetts Institute of Technology, Cambridge, MA Teaching Assistant for The Analytics Edge (15.071) 2017 edX, Cambridge, MA Teaching Assistant for The Analytics Edge (15.071x)

2016 Massachusetts Institute of Technology, Cambridge, MA Teaching Assistant for Data, Models, and Decisions (15.060) Publications

"Data-driven transit network design at scale”, with Dimitris Bertsimas and Yee Sian Ng, working paper.

"Frequency-setting and pricing optimization on multi-modal transit networks at scale”, with Dimitris Bertsimas and Yee Sian Ng, submitted to Transportation Science, 2018. "Prescriptive analytics for human resource planning in the professional services industry”, with Lauren Berk, Dimitris Bertsimas, and Alexander Weinstein, in European Journal of Operations Research, 2019.

"From physical properties of transportation flows to demand estimation: An optimization approach”, with Dimitris Bertsimas, in Transportation Science, 2018. "Optimal nonlinear coherent mode transitions in Bose-Einstein condensates utilizing spatiotemporal controls”, with David Hocker and Herschel Rabitz, in Physical Review A, 2016.

”Exploring the Control Landscape for Nonlinear Quantum Dynamics”, with David Hocker, Ruixing Long, Tak-San Ho, and Herschel Rabitz, in Physical Review A, 2014.

Honors and Awards 2013 Phi Beta Kappa

Princeton University 2013 Robert T. McCay Prize

Princeton University Department of Chemistry 2012 William Foster Memorial Prize Princeton University Department of Chemistry 2010 Shapiro Prize for Academic Excellence

Princeton University Skills and Activities

Programming: Julia, R, Java, C, MATLAB, SQL Languages: Mandarin Chinese (conversational), French (novice)


Kevin Zhang


10 Stanford Terrace Somerville, MA 02143

816-588-2869

Education Massachusetts Institute of Technology, Cambridge, MA Candidate for PhD in Operations Research; expected completion, June 2019. GPA: 5.0/5.0 Advisor: Prof. Carolina Osorio Yale University, New Haven, CT

BS cum laude in Mathematics and Statistics, with distinction in both majors, May 2012. GPA: 3.83/4.00, Department GPA: 3.94/4.00

Work Experience 2012-2014 Analytics Operations Engineering, Inc. (acquired by McKinsey & Company), Boston, MA Operations Research Analyst

Worked on teams of two to six consultants to help clients solve operations problems like improving productivity, lowering costs, and increasing capacity through mathematical modeling, programming, and data-driven decision analysis. Projects included: guiding marketing strategy across print, email, and web channels for a $12B+ retail company; forecasting customer demand and inventory shipments to reduce safety stock levels at a Canadian food distribution company; implementing an inventory allocation tool in newly opened stores for a retail clothing chain; predicting customer repayment behavior for a nationwide loan provider.

2011 Federal Reserve Bank, Kansas City, MO (Summer) Economic Research Intern

Conducted an independent research project on the properties of peer-to-peer (P2P) payment services markets. Developed a game theoretic model for P2P markets based on recent research on network goods and social networks, and investigated sensitivity to market share and pricing through simulation experiments.

2010 National Security Agency, Fort Meade, MD (Summer) Intern, Director’s Summer Program

Collaborated with two fellow interns, with support from three agency researchers, on a 10-week long project. Developed methods to attack a sophisticated cryptographic system through application of linear algebra, abstract algebra, and statistics. Published a technical paper for internal use and briefed the Deputy Director of NSA on summer work.


Research Assistant Advisor: Prof. Carolina Osorio

Working on large-scale stochastic optimization problems as applied to calibration of traffic simulators. Developing computationally efficient methods for online calibration that incorporate network-specific structural information into Kalman filtering algorithms.

2012 Yale University, New Haven, CT

Senior Project – Statistics Department Supervisor: Prof. Jing Zhang Conducted a genome-wide association study of type 2 diabetes using a block-based Bayesian model and applied our method to a case-control dataset from the Wellcome Trust Case Control Consortium.

2009 Yale University, New Haven, CT

Summer Research Supervisor: Prof. Hisham Sati Worked with four undergraduates to develop a consistent representational system for the action of Lie groups on hypermatrices and to investigate the invariance properties of hypermatrices.

Teaching Experience 2017 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Transportation Systems Analysis: Performance and Optimization

(1.200/11.544) Led weekly one-hour TA sessions, held office hours, and developed problem sets and quizzes for first-year graduate level course. Same topics as previous year.

2016 Massachusetts Institute of Technology, Cambridge, MA (Fall) Teaching Assistant for Transportation Systems Analysis: Performance and Optimization

(1.200/11.544) Led weekly one-hour TA sessions, held office hours, and developed problem sets and quizzes for first-year graduate level course. Topics include: traffic flow analysis, deterministic and probabilistic delay models, linear and integer optimization methods, queueing networks, and stochastic simulation. Overall student rating: 6.6/7.0.

Presentations

“Enhancing the computational efficiency of online calibration techniques for traffic simulators”, with C. Osorio, presented at INFORMS 2016, Nashville, TN.

“Combining data-driven and model-driven approaches for traffic simulator calibration problems”, with C. Osorio, presented at INFORMS 2015, Philadelphia, PA.

Honors and Awards 2012 Second Prize at the International Mathematics Competition for University Students 2010 Benjamin F. Barge Prize for solution of original problems in mathematics 2009 Charles M. Runk Prize for demonstrating excellence in a competitive examination in mathematics 2009 Dean’s Research Fellowship in the Sciences


Programming: R, Matlab, Python, SQL, Java, VBA, C Languages: English (native)

Citizenship Citizen of the United States of America

operations research centersinghvi, 2017, major revision in operations research (with johnson &...

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