computer science & engineering - 2019-20...

Bul le t in 2020-21Computer Sc ience & Engineer ing (08 /03 /20)

Computer Science &EngineeringAbout Computer Science &EngineeringThe field of computer science and engineering studies thedesign, analysis, implementation and application of computationand computer technology. Computing plays an important rolein virtually all fields, including science, medicine, music, art,business, law and human communication; hence, the study ofcomputer science and engineering can be interdisciplinary innature. Whether a student's goal is to become a practitioneror to take a few courses to develop a basic understanding ofcomputing for application to another field, the Department ofComputer Science & Engineering at Washington University iscommitted to helping students gain the background they need.

People are attracted to the study of computing for a variety ofreasons. Consequently, the department offers a wide varietyof academic programs, including a five-course minor, a secondmajor, five undergraduate degrees, combined undergraduateand graduate programs, and several undergraduate researchopportunities. Each academic program can be tailored to astudent's individual needs.

The breadth of computer science and engineering may bebest understood in terms of the general areas of applications,software systems, hardware and theory.

Applications are the ways in which computer technologyis applied to solve problems, often in other disciplines. Mostapplications courses provide background not only in theapplications themselves but also in how the applications aredesigned and implemented. Examples of application areasinclude artificial intelligence, computer graphics, game designand computational biology.

Software systems are collections of interacting softwarecomponents that work together to support the needs of computerapplications. Courses in this area help students gain a solidunderstanding of how software systems are designed andimplemented. During the process, students develop their ownsoftware systems. Examples include operating systems, whichmanage computational resources; network protocols, whichare responsible for the delivery of information; programminglanguages, which support the construction of software systemsand applications; and compilers, which translate computerprograms into executable form.

Hardware is the term used to describe the physical andmechanical components of a computer system. Courses inthis area provide background in logic circuits, which carry outbasic computations; computer architecture, which defines theorganization of functional components in a computer system;

and peripheral devices such as disks, robot arms that arecontrolled by the computer system, and sensor systems thatgather the information that computer systems use to interact withthe physical world.

Theory is the study of the fundamental capabilities andlimitations of computer systems. A knowledge of theory helpsstudents choose among competing design alternatives on thebasis of their relative efficiency and helps them to verify thattheir implementations are correct. Theory courses providebackground in algorithms, which describe how a computation isto be carried out; data structures, which specify how informationis to be organized within the computer; analytical techniques tocharacterize the time or space requirements of an algorithm ordata structure; and verification techniques to prove that solutionsare correct.

A well-rounded study of computing includes training in each ofthese areas. However, depending on a student's educationalgoals, the student may prefer to concentrate on certain areasfor greater depth of knowledge. To help students balance theirelective courses, most upper-level departmental courses areclassified into one of the following categories: S for softwaresystems, M for machines (hardware), T for theory, or A forapplications. If a student's interests are concentrated in thefirst two areas, a computer engineering degree might be best.Students are encouraged to meet with a faculty adviser in theDepartment of Computer Science & Engineering to discuss theiroptions and develop a plan consistent with their goals.

Undergraduate ProgramsThe Department of Computer Science & Engineering (CSE)offers an array of courses that can be taken as requirementsor electives for any of the undergraduate degree programs.We offer a Bachelor of Science in Computer Science (BSCS),a Bachelor of Science in Computer Engineering (BSCoE), aBachelor of Science in Business and Computer Science (CS+Business), a Bachelor of Science in Computer Science +Mathematics (CS+Math), a Bachelor of Science in ComputerScience + Economics (CS+Econ), and a Second Major inComputer Science. In addition to these six programs, CSE offersa pre-medical option and combined undergraduate/graduateprograms. As a part of our program, each student is assignedan adviser who can help to design an individualized program,monitor a student's progress, and consult about curriculum andcareer options. Additional information can be found on our CSEwebsite (http://cse.wustl.edu), or any of the CSE faculty (https://cse.wustl.edu/faculty/Pages/default.aspx) can offer furtherguidance and information about our programs.

BSCS: The computer science (https://cse.wustl.edu/undergraduate/programs/Pages/bs-in-computer-science.aspx)major is designed for students planning a career in computing.

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BSCoE: The computer engineering (https://cse.wustl.edu/undergraduate/programs/Pages/bs-in-computer-engineering.aspx) major encompasses studies of hardware,software and systems issues that arise in the design,development and application of computer systems.

CS+Business: This joint major (https://cse.wustl.edu/undergraduate/programs/Pages/bs-business-computer-science.aspx) provides students with the fundamental knowledgeand perspectives of computer science and business and of theunique opportunities created by combining them.

CS+Econ: This applied science major (http://bulletin.wustl.edu/undergrad/engineering/computerscience/bs-applied-computer-science-economics) allows students interested in botheconomics and computer science to combine these twocomplementary disciplines efficiently.

CS+Math: This applied science major (https://cse.wustl.edu/undergraduate/programs/Pages/bs-in-computer-science-math.aspx) efficiently captures the intersection of thecomplementary studies of computer science and math.

Second Major in Computer Science: The second major(https://cse.wustl.edu/undergraduate/programs/Pages/second-major.aspx) provides an opportunity to combine computerscience with another degree program. A second major incomputer science can expand a student's career options andenable interdisciplinary study in areas such as cognitive science,computational biology, chemistry, physics, philosophy andlinguistics. The second major is also well suited for studentsplanning careers in medicine, law, business, architecture andfine arts.

Pre-Medical Option within Computer Science: Students maypursue a pre-medicine curriculum in conjunction with either theBS degree or the second major in computer science programs.Students interested in the pre-medical option should refer tothe McKelvey School of Engineering (http://bulletin.wustl.edu/undergrad/engineering/#premedicaleducation) Bulletin page fordetails.

Combined Undergraduate andGraduate StudyThe Department of Computer Science & Engineering offersin-depth graduate study in many areas. Students entering thegraduate programs require a background in computer sciencefundamentals. Washington University undergraduates seekingadmission to the graduate degree program to obtain a master'sdegree in computer science or computer engineering do notneed to take the Graduate Record Examination (GRE). Formore information, contact the department office by email [email protected] or by phone at 314-935-6132.

The Joint Bachelor's/Master's ProgramThis five-year program that leads to both the bachelor's andmaster's degrees offers the student an excellent opportunity tocombine undergraduate and graduate studies in an integratedcurriculum. The combination of the two programs extends theflexibility of the undergraduate curriculum to more advancedstudies, thereby enabling students to plan their entire spectrumof computing studies in a more comprehensive educationalframework. Consistent with the general requirements (http://bulletin.wustl.edu/undergrad/engineering/requirements) definedby the McKelvey School of Engineering, a minimum of 150 unitsis required for completion of the bachelor's/master's program.Provided that the 150-unit requirement is satisfied, up to 6units of course work acceptable for the master's degree can becounted toward both the bachelor's and master's requirements.Students in the bachelor's/master's program can take advantageof the program's flexibility by taking graduate courses toward thegraduate degree while still completing the undergraduate degreerequirements.

The bachelor's/master's program offers early admission tothe graduate programs in computer science and computerengineering and allows a student to complete the master'sdegree, typically in only one additional year of study (insteadof the usual three semesters). Undergraduate financial supportis not extended for the additional semesters to complete themaster's degree requirements; however, scholarship supportbased on the student's cumulative grade-point average,calculated at the end of the junior year, will be awardedautomatically during the student's final year of study. Studentsare classified as graduate students during their final year ofstudy, and their tuition charges are at the graduate student rate.For information about scholarship amounts, please visit theBachelor's/Master's Program in Engineering webpage (http://engineering.wustl.edu/current-students/student-services/Pages/BS-MS-program.aspx).

If students plan to apply to this program, it is recommendedthat they complete at least an undergraduate minor in computerscience, three additional computer science courses at the 400level, and one additional course at the 500 level during their firstfour years. Fall applications for this program open on June 1.Spring applications open on March 1. Students are encouragedto apply to this program by October 1 of the first semester oftheir senior year, and a minimum GPA of 3.0 is required of allapplicants. Bachelor's/master's applications will be accepteduntil the last day of classes of the semester prior to the studentbeginning the graduate program.

BS/MBA ProgramThe growing importance of computer-based information systemsin the business environment has produced a sustained highdemand for graduates with master's degrees in businessadministration and undergraduate majors in computer scienceand engineering.

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Students should apply to this joint program by February 1of their junior year. The application for admission to OlinBusiness School (http://bulletin.wustl.edu/undergrad/business) isavailable through the business school. Applicants are judged onundergraduate performance, GMAT scores, summer and/or co-op work experience, recommendations and a personal interview.

Undergraduate CoursesCourse requirements for the minor and majors may be fulfilledby CSE 131 Introduction to Computer Science, CSE 132Introduction to Computer Engineering, CSE 240 Logicand Discrete Mathematics, CSE 247 Data Structures andAlgorithms, CSE 347 Analysis of Algorithms, and CSE courseswith a letter suffix in any of the following categories: softwaresystems (S), hardware (M), theory (T) and applications (A).In addition, with approval of the instructor, up to 6 unitsof CSE 400E Independent Study can be used toward the CSEelectives of any CSE degree. Other CSE courses provide credittoward graduation but not toward the CSE elective requirementsfor the second major or the BSCS, BSCoE, CS+Math or CS+Business degrees. Undergraduates are encouraged to consider500-level courses. If a student is interested in taking a coursebut is not sure if they have the needed prerequisites, the studentshould contact the instructor.

Broadening ExperiencesIf a student wants to become involved in computer science orcomputer engineering research or to gain experience in industrywhile they are an undergraduate, there are many opportunities todo so. A few of these are listed below.

Co-op: The Cooperative Education Program allows a studentto get valuable experience working in industry while anundergraduate. A co-op experience can give students anotherperspective on their education and may lead to full-timeemployment. Numerous companies participate in this program.More information is available from the Engineering Co-opand Internship Program (https://careercenter.wustl.edu/items/engineering-co-op-program) that is part of the Career Center inthe Danforth University Center, Suite 110.

Research: Participating in undergraduate research (https://cse.wustl.edu/undergraduate/Pages/undergraduate-research.aspx) is a great way to learn more about a specificarea. Research projects are available either for pay or for creditthrough CSE 400E Independent Study.

Study Abroad: Students in the McKelvey School of Engineeringcan study abroad in a number of countries and participate inseveral global experiences to help broaden their educationalexperience. These opportunities will help students becomeglobal citizens who are better able to address current issues.

The study of computer science and engineering is especiallywell suited and popular for study abroad. Students from ourdepartment routinely study abroad in Europe, the UnitedKingdom, Australia, Israel and many other places. Ourdepartment works closely with students to identify coursessuitable for computer science credit.

For more information about these programs, please visitthe McKelvey School of Engineering website (https://engineering.wustl.edu/our-school/initiatives/Pages/global.aspx).

Research OpportunitiesThe Department of Computer Science & Engineering activelypromotes a culture of strong undergraduate participation inresearch. Many undergraduates work in research labs withstate-of-the-art equipment that provides them the opportunityto take part in computer science and computer engineeringresearch. Sensor networks, high-speed routers, specializedFPGA hardware, wireless devices, RF tags, digital cameras,robots, large displays and multiprocessors are just a few of thehardware devices undergraduates often use in their projects.Opportunities for exploring modern software developmenttechniques and specialized software systems further enrich therange of research options and help undergraduates sharpentheir design and programming skills.

Advanced Placement/ProficiencyStudents receiving a 4 or 5 on the AP Computer Science Aexam are awarded credit for CSE 131 Introduction to ComputerScience. Any student can take the CSE 131 proficiency exam,and a suitable score will waive CSE 131 as a requirement.

Upon request, the computer science department will evaluatea student for proficiency for any of our introductory courses. Ifa student is determined to be proficient in a given course, thatcourse will be waived (without awarding credit) in the student'sdegree requirements, and the student will be offered guidance inselecting a more advanced course. Questions should be directedto the associate chair at [email protected].

Phone: 314-935-6160

Website: https://cse.wustl.edu/undergraduate/programs

FacultyChairRoch Guérin (https://engineering.wustl.edu/Profiles/Pages/Roch-Gu%C3%A9rin.aspx)Harold B. and Adelaide G. Welge Professor of ComputerSciencePhD, California Institute of TechnologyComputer networks and communication systems

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ProfessorsSanjoy Baruah (https://engineering.wustl.edu/Profiles/Pages/Sanjoy-Baruah.aspx)PhD, University of Texas at AustinReal-time and safety-critical system design, cyber-physicalsystems, scheduling theory, resource allocation and sharing indistributed computing environments

Aaron Bobick (https://engineering.wustl.edu/Profiles/Pages/Aaron-Bobick.aspx)James M. McKelvey Professor and DeanPhD, Massachusetts Institute of TechnologyComputer vision, graphics, human-robot collaboration

Michael R. Brent (https://engineering.wustl.edu/Profiles/Pages/Michael-Brent.aspx)Henry Edwin Sever Professor of EngineeringPhD, Massachusetts Institute of TechnologySystems biology, computational and experimental genomics,mathematical modeling, algorithms for computational biology,bioinformatics

Jeremy Buhler (https://engineering.wustl.edu/Profiles/Pages/Jeremy-Buhler.aspx)PhD, Washington UniversityComputational biology, genomics, algorithms for comparing andannotating large biosequences

Roger D. Chamberlain (https://engineering.wustl.edu/Profiles/Pages/Roger-Chamberlain.aspx)DSc, Washington UniversityComputer engineering, parallel computation, computerarchitecture, multiprocessor systems

Yixin Chen (https://engineering.wustl.edu/Profiles/Pages/Yixin-Chen.aspx)PhD, University of Illinois at Urbana-ChampaignMathematical optimization, artificial intelligence, planning andscheduling, data mining, learning data warehousing, operationsresearch, data security

Patrick Crowley (https://engineering.wustl.edu/Profiles/Pages/Patrick-Crowley.aspx)PhD, University of WashingtonComputer and network systems, network security

Ron K. Cytron (https://engineering.wustl.edu/Profiles/Pages/Ron-Cytron.aspx)PhD, University of Illinois at Urbana-ChampaignProgramming languages, middleware, real-time systems

Christopher D. Gill (https://engineering.wustl.edu/Profiles/Pages/Christopher-Gill.aspx)DSc, Washington UniversityParallel and distributed real-time embedded systems, cyber-physical systems, concurrency platforms and middleware, formalmodels and analysis of concurrency and timing

Sanmay Das (https://engineering.wustl.edu/Profiles/Pages/Sanmay-Das.aspx)PhD, Massachusetts Institute of TechnologyDesign of algorithms for complex environments, computationalsocial science, machine learning

Raj Jain (https://engineering.wustl.edu/Profiles/Pages/Raj-Jain.aspx)Barbara J. & Jerome R. Cox Jr. Professor of Computer SciencePhD, Harvard UniversityNetwork security, blockchains, medical systems security,industrial systems security, wireless networks, unmanned aircraftsystems, internet of things, telecommunications networks, trafficmanagement

Tao Ju (https://engineering.wustl.edu/Profiles/Pages/Tao-Ju.aspx)PhD, Rice UniversityComputer graphics, visualization, mesh processing, medicalimaging and modeling

Chenyang Lu (https://engineering.wustl.edu/Profiles/Pages/Chenyang-Lu.aspx)Fullgraf Professor in the Department of Computer Science &EngineeringPhD, University of VirginiaInternet of things, real-time, embedded, and cyber-physicalsystems, cloud and edge computing, wireless sensor networks

Neal Patwari (https://engineering.wustl.edu/Profiles/Pages/Neal-Patwari.aspx)PhD, University of MichiganApplication of statistical signal processing to wireless networks,and radio frequency signals

Weixiong ZhangPhD, University of California, Los AngelesComputational biology, genomics, machine learning and datamining, and combinatorial optimization

Associate ProfessorsKunal Agrawal (https://engineering.wustl.edu/Profiles/Pages/Kunal-Agrawal.aspx)PhD, Massachusetts Institute of TechnologyParallel computing, cyber-physical systems & sensing,theoretical computer science

Caitlin Kelleher (https://engineering.wustl.edu/Profiles/Pages/Caitlin-Kelleher.aspx)Hugo F. & Ina Champ Urbauer Career Development AssociateProfessorPhD, Carnegie Mellon UniversityHuman-computer interaction, programming environments, andlearning environments

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William D. Richard (https://engineering.wustl.edu/Profiles/Pages/William-Richard.aspx)PhD, University of Missouri-RollaUltrasonic imaging, medical instrumentation, computerengineering

Yevgeniy Vorobeychik (https://cse.wustl.edu/faculty/Pages/faculty.aspx?bio=185)PhD, University of MichiganArtificial intelligence, machine learning, computationaleconomics, security and privacy, multi-agent systems

William Yeoh (https://engineering.wustl.edu/Profiles/Pages/William-Yeoh.aspx)PhD, University of Southern CaliforniaArtificial intelligence, multi-agent systems, distributed constraintoptimization, planning and scheduling

Assistant ProfessorsAyan Chakrabarti (https://engineering.wustl.edu/Profiles/Pages/Ayan-Chakrabarti.aspx)PhD, Harvard UniversityComputer vision computational photography, machine learning

Roman Garnett (https://engineering.wustl.edu/Profiles/Pages/Roman-Garnett.aspx)PhD, University of OxfordActive learning (especially with atypical objectives), Bayesianoptimization, and Bayesian nonparametric analysis

Chien-Ju Ho (https://engineering.wustl.edu/Profiles/Pages/Chien-Ju-Ho.aspx)PhD, University of California, Los AngelesDesign and analysis of human-in-the-loop systems, withtechniques from machine learning, algorithmic economics, andonline behavioral social science

Brendan Juba (https://engineering.wustl.edu/Profiles/Pages/Brendan-Juba.aspx)PhD, Massachusetts Institute of TechnologyTheoretical approaches to artificial intelligence founded oncomputational complexity theory and theoretical computerscience more broadly construed

Ulugbek Kamilov (https://engineering.wustl.edu/Profiles/Pages/Ulugbek-Kamilov.aspx)PhD, École Polytechnique Fédérale de Lausanne, SwitzerlandComputational imaging, image and signal processing, machinelearning and optimization

Angelina Lee (https://engineering.wustl.edu/Profiles/Pages/I-Ting-Angelina-Lee.aspx)PhD, Massachusetts Institute of TechnologyDesigning linguistics for parallel programming, developingruntime system support for multithreaded software, and buildingnovel mechanisms in operating systems and hardware toefficiently support parallel abstractions

Alvitta Ottley (https://cse.wustl.edu/faculty/Pages/faculty.aspx?bio=109)PhD, Tufts UniversityDesigning personalized and adaptive visualization systems,including information visualization, human-computer interaction,visual analytics, individual differences, personality, usermodeling and adaptive interfaces

Netanel Raviv (https://cse.wustl.edu/faculty/Pages/faculty.aspx?bio=197)PhD, Technion, Haifa, IsraelMathematical tools for computation, privacy and machinelearning

Ning Zhang (https://cse.wustl.edu/faculty/Pages/faculty.aspx?bio=182)PhD, Virginia Polytechnic Institute and State UniversitySystem security, software security

Teaching ProfessorWilliam Siever (https://cse.wustl.edu/faculty/Pages/Bill-Siever.aspx)PhD, Missouri University of Science and TechnologyComputer architecture, organization, and embedded systems

Todd Sproull (https://cse.wustl.edu/faculty/Pages/Todd-Sproull.aspx)PhD, Washington UniversityComputer networking and mobile application development

Professor of the PracticeDennis Cosgrove (https://cse.wustl.edu/faculty/Pages/Dennis-Cosgrove.aspx)BS, University of VirginiaProgramming environments and parallel programming

LecturersHila Ben Abraham, LecturerPhD, Washington University in St. LouisParallel computing, accelerating streaming applications onGPUs, computer and network security, malware analysis

Steve Cole, Senior LecturerPhD, Washington University in St. LouisParallel computing, accelerating streaming applications on GPUs

Brian Garnett (https://cse.wustl.edu/faculty/Pages/faculty.aspx?bio=204), LecturerPhD, Rutgers UniversityDiscrete mathematics and probability, generally motivated bytheoretical computer science

Marion Neumann (https://cse.wustl.edu/faculty/Pages/Marion-Neumann.aspx), Senior LecturerPhD, University of Bonn, GermanyMachine learning with graphs; solving problems in agricultureand robotics

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James Orr, LecturerPhD, Washington UniversityReal-time systems theory and implementation, cyber-physicalsystems, and operating systems

Jonathan Shidal (https://cse.wustl.edu/faculty/Pages/Jon-Shidal.aspx), LecturerPhD, Washington UniversityComputer architecture and memory management

Douglas Shook (https://cse.wustl.edu/faculty/Pages/Doug-Shook.aspx), Senior LecturerMS, Washington UniversityImaging sensor design, compiler design and optimization

Senior ProfessorsJonathan S. TurnerPhD, Northwestern UniversityDesign and analysis of internet routers and switching systems,networking and communications, algorithms

Senior Faculty EmeritusJerome R. Cox Jr.ScD, Massachusetts Institute of TechnologyComputer system design, computer networking, biomedicalcomputing

Professors EmeritiTakayuki D. KimuraPhD, University of PennsylvaniaCommunication and computation, visual programming

Seymour V. PollackMS, Brooklyn Polytechnic InstituteIntellectual property, information systems

MajorsPlease visit the following pages for information about computerscience and engineering majors:

• Bachelor of Science in Computer Engineering (http://bulletin.wustl.edu/undergrad/engineering/computerscience/bs-computer-engineering)

• Bachelor of Science in Computer Science (http://bulletin.wustl.edu/undergrad/engineering/computerscience/bs-computer-science)

• Bachelor of Science in Computer Science + Economics(http://bulletin.wustl.edu/undergrad/engineering/computerscience/bs-applied-computer-science-economics)

• Bachelor of Science in Computer Science + Mathematics(http://bulletin.wustl.edu/undergrad/engineering/computerscience/bs-applied-computer-science-math)

• Bachelor of Science in Business and Computer Science(http://bulletin.wustl.edu/undergrad/engineering/computerscience/bs-business-computer-science)

• Second Major in Computer Science (http://bulletin.wustl.edu/undergrad/engineering/computerscience/second-major)

• Second Major in Computer Science + Mathematics

MinorsPlease visit the following pages for information about computerscience and engineering minors:

• Minor in Computer Science (http://bulletin.wustl.edu/undergrad/engineering/computerscience/minor-computer-science)

• Minor in Bioinformatics (http://bulletin.wustl.edu/undergrad/engineering/computerscience/minor-bioinformatics)

• Minor in Human-Computer Interaction (http://bulletin.wustl.edu/undergrad/engineering/computerscience/minor-human-computer-interaction)

CoursesVisit online course listings to view semester offerings forE81 CSE (https://courses.wustl.edu/CourseInfo.aspx?sch=E&dept=E81&crslvl=1:5).

Prerequisites are advisory in our course listings, but studentsare cautioned against taking a course without the necessarybackground. Note that if one course mentions another as itsprerequisite, the prerequisites of the latter course are implied tobe prerequisites of the former course as well. Students in doubtof possessing the necessary background for a course shouldcorrespond with the course's instructor.

E81 CSE 131 Introduction to Computer ScienceAn introduction to software concepts and implementation,emphasizing problem solving through abstraction anddecomposition. Introduces processes and algorithms, proceduralabstraction, data abstraction, encapsulation and object-orientedprogramming. Recursion, iteration and simple data structures arecovered. Concepts and skills are mastered through programmingprojects, many of which employ graphics to enhance conceptualunderstanding. Java, an object-oriented programming language,is the vehicle of exploration. Active-learning sessions areconducted in a studio setting in which students interact witheach other and the professor to solve problems collaboratively.Prerequisites: Comfort with algebra and geometry at thehigh school level is assumed. Patience, good planning andorganization promote success. This course assumes no priorexperience with programming.Credit 3 units. BU: SCI EN: TU

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E81 CSE 131R Seminar: Computer Science IA seminar and discussion session that complements the materialstudied in CSE 131. Provides background and breadth for thedisciplines of computer science and computer engineering.Features guest lectures and highly interactive discussions ofdiverse computer science topics. Highly recommended formajors and for any student seeking a broader view of computerscience or computer engineering. Pass/Fail only.Credit 1 unit.

E81 CSE 132 Introduction to Computer EngineeringThis course introduces students to fundamental concepts inthe basic operation of computers, ranging from desktops andservers to microcontrollers and handheld devices. Subjectsinclude digital and analog input/output, sensing the physicalworld, information representation, basic computer architectureand machine language, time-critical computation, machine-to-machine communication and protocol design. Students willuse both desktop systems and handheld microcontrollers forlaboratory experiments. Active-learning sessions are conductedin a studio setting in which students interact with each other andthe professor to solve problems collaboratively. Prerequisite:CSE 131.Credit 3 units. BU: SCI EN: TU

E81 CSE 132R Seminar: Computer Science IIThis course is a seminar and discussion session thatcomplements the material studied in CSE 132. It providesbackground and breadth for the disciplines of computer scienceand computer engineering, and it features guest lectures andhighly interactive discussions of diverse computer science topics.Highly recommended for majors and for any student seeking abroader view of computer science or computer engineering.Credit 1 unit.

E81 CSE 204A Front-End Web DevelopmentThis course explores elementary principles for designing,creating, and publishing effective websites and web applicationfront-ends. Topics include page layout concepts, designprinciples, HTML, CSS, JavaScript, front-end frameworks likeAngular and React, and other development tools. Students applythe topics by creating a series of websites that are judged basedon their design and implementation. Prerequisite: CSE 131 orequivalent experience.Credit 3 units. EN: TU

E81 CSE 217A Introduction to Data ScienceThis course provides an introduction to data science andmachine learning, and it focuses on the practical applicationof models to real-world supervised and unsupervised learningproblems. We will discuss methods for linear regression,classification, and clustering and apply them to performsentiment analysis, implement a recommendation system, andperform image classification or gesture recognition. One of themain objectives of the course is to become familiar with the datascience workflow, from posing a problem to understanding andpreparing the data, training and evaluating a model, and thenpresenting and interpreting the results. We will also touch onconcepts such as similarity-based learning, feature engineering,data manipulation, and visualization. The course uses Python,which is currently the most popular programming language fordata science. Prerequisites: CSE 131, MATH 233, and CSE 247(can be taken concurrently)Credit 3 units. EN: TU

E81 CSE 222S Internet of ThingsWith the advent of the Internet of Things, we can address,control, and interconnect formerly isolated objects to createnew and interesting applications. In this course we studyfundamental technologies behind Internet-of-Things devices, andAppcessories, which include smart watches, health monitors,toys, and appliances. In addition to learning about IoT, studentsgain hands-on experience developing multi-platform solutionsthat control and communicate with Things using via mobiledevice friendly interfaces. Students apply their knowledge andskill to develop a project of their choosing using topics from thecourse. Prerequisite: CSE 132 Revision: 2020-02-26Credit 3 units. EN: TU

E81 CSE 231S Introduction to Parallel and ConcurrentProgrammingThis course explores concepts, techniques, and designapproaches for parallel and concurrent programming. We studyhow to write programs that make use of multiple processorsfor responsiveness and that share resources reliably and fairly.Parallel programming concepts include task-level, functional, andloop-level parallelism. Concurrent programming concepts includethreads, synchronization, and locks. We cover how to adaptalgorithms to achieve determinism and avoid data races anddeadlock. Concepts and skills are acquired through the designand implementation of software projects. Prerequisite: CSE 131.Credit 3 units. EN: TU

E81 CSE 232 Programming Skills WorkshopThis course provides an overview of practical implementationskills. Topics include compilation and linking, memorymanagement, pointers and references, using code libraries,testing and debugging. Prerequisite: CSE 247.Credit 1 unit.

E81 CSE 240 Logic and Discrete MathematicsIntroduces elements of logic and discrete mathematics thatallow reasoning about computational structures and processes.Generally, the areas of discrete structures, proof techniques,probability and computational models are covered. Topicstypically include propositional and predicate logic; sets, relations,functions and graphs; proof by contradiction, induction andrecursion; finite state machines and regular languages; andintroduction to discrete probability, expected value and variance.Prerequisite: CSE 131.Credit 3 units. EN: TU

E81 CSE 247 Data Structures and AlgorithmsThis course involves the study of fundamental algorithms, datastructures, and their effective use in a variety of applications.It emphasizes the importance of data structure choice andimplementation for obtaining the most efficient algorithm forsolving a given problem. A key component of this course isworst-case asymptotic analysis, which provides a quick andsimple method for determining the scalability and effectivenessof an algorithm. Prerequisite: CSE 131 and fluency withsummations, derivatives, and proofs by induction.Credit 3 units. EN: TU

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E81 CSE 247R Seminar: Data Structures and AlgorithmsThe content of this seminar will vary by semester, but it willgenerally complement the material taught in CSE 247 DataStructures and Algorithms. Corequisite: CSE 247.Credit 1 unit. EN: TU

E81 CSE 256A Introduction to Human-Centered DesignThis course provides an introduction to human-centered designthrough a series of small user interface development projectscovering usability topics such as efficiency vs. learnability, walkup and use systems, the habit loop, and information foraging.Projects will begin with reviewing a relevant model of humanbehavior. Each project will then provide an opportunity to explorehow to apply that model in the design of a new user interface.Prerequisite: CSE 131.Credit 3 units. EN: TU

E81 CSE 260M Introduction to Digital Logic and ComputerDesignIntroduction to design methods for digital logic and fundamentalsof computer architecture. Boolean algebra and logic minimizationtechniques; sources of delay in combinational circuits andeffect on circuit performance; survey of common combinationalcircuit components; sequential circuit design and analysis;timing analysis of sequential circuits; use of computer-aideddesign tools for digital logic design (schematic capture,hardware description languages, simulation); design of simpleprocessors and memory subsystems; program execution insimple processors; basic techniques for enhancing processorperformance; configurable logic devices. Prerequisites: CSE131.Credit 3 units. EN: TU

E81 CSE 311A Introduction to Intelligent Agents UsingScience FictionThe course uses science-fiction short stories, tv episodes,and movies to motivate and introduce fundamental principlesand techniques in intelligent agent systems. Topics coveredmay include game theory, decision theory, machine learning,distributed algorithms, and ethics. Prerequisite: CSE 247Credit 3 units. EN: BME T, TU

E81 CSE 316A Social Network AnalysisThis course looks at social networks and markets through theeyes of a computer scientist. We will look at questions including,"Why are acquaintances rather than friends more likely to get usjob opportunities?" and, "Why do the rich get richer?" We beginby studying graph theory (allowing us to study the structure)and game theory (allowing us to study the interactions) of socialnetworks and market behavior at the introductory level. Amongother topics, we will study auctions, epidemics, and the structureof the internet (including web searches). This course examinesthe intersection of computer science, economics, sociology, andapplied mathematics. Prerequisites: CSE 240 and CSE 247.Credit 3 units. EN: BME T, TU

E81 CSE 330S Rapid Prototype Development and CreativeProgrammingThis course uses web development as a vehicle for developingskills in rapid prototyping. Students acquire the skills to build aLinux web server in Apache, to write a website from scratch inPHP, to run an SQL database, to perform scripting in Python, to

employ various web frameworks, and to develop modern webapplications in client-side and server-side JavaScript. The courseculminates with a creative project in which students are able tosynthesize the course material into a project of their own interest.The course implements an interactive studio format: after theformal presentation of a topic, students develop a related projectunder the supervision of the instructor. Prerequisite: CSE 131.Credit 3 units. EN: BME T, TU

E81 CSE 332S Object-Oriented Software DevelopmentLaboratoryIntensive focus on practical aspects of designing, implementingand debugging software, using object-oriented, procedural,and generic programming techniques. The course emphasizesfamiliarity and proficiency with a wide range of C++ languagefeatures through hands-on practice completing studio exercisesand lab assignments, supplemented with readings and summarypresentations for each session. Prerequisites: CSE 131 and CSE247Credit 3 units. EN: BME T, TU

E81 CSE 341T Parallel and Sequential AlgorithmsThe course aims to teach how to design, analyze and implementparallel algorithms. The emphasis is on teaching fundamentalprinciples and design techniques that easily transfer over toparallel programming. These techniques include divide andconquer, contraction, the greedy method, etc. Prerequisite: CSE240, 247, Math 310Credit 3 units. EN: BME T, TU

E81 CSE 347 Analysis of AlgorithmsIntroduces techniques for the mathematical analysis ofalgorithms, including randomized algorithms and non-worst-caseanalyses such as amortized and competitive analysis. Introducesthe standard paradigms of divide-and-conquer, greedy, anddynamic programming algorithms, as well as reductions.Also provides an introduction to the study of intractability andtechniques to determine when good algorithms cannot bedesigned. Prerequisites: CSE 240, 247 (or Math 310).Credit 3 units. EN: BME T, TU

E81 CSE 347R Analysis of Algorithms RecitationThis course is the recitation component of CSE 347. Registrationand attendance for 347R is mandatory for students enrolled in347.

E81 CSE 361S Introduction to Systems SoftwareIIntroduction to the hardware and software foundationsof computer processing systems. This course provides aprogrammer's perspective of how computer systems executeprograms and store information. The course material aimsto enables students to become more effective programmers,especially in dealing with issues of performance, portabilityand robustness. It also serves as a foundation for other systemcourses, such as compilers, networks, and operating systems,where a deeper understanding of systems-level issues isrequired. Topics covered include: machine-level code and itsgeneration by optimizing compilers, performance evaluationand optimization, computer arithmetic, memory organizationand management, and supporting concurrent computation.Prerequisites: CSE 131 and CSE 132Credit 3 units. EN: BME T, TU

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E81 CSE 362M Computer ArchitectureThis course explores the interaction and design philosophyof hardware and software for digital computer systems.Topics include: processor architecture, instruction setarchitecture, Assembly Language, memory hierarchy design, I/O considerations, and a comparison of computer architectures.Prerequisite: CSE 260M.Credit 3 units. EN: BME T, TU

E81 CSE 365S Elements of Computing SystemsAll computers are made up of 0s and 1s. However, theconceptual gap between the 0s and 1s and the day-to-dayoperation of modern computers is enormously wide. This fast-paced course aims to bridge the divide by starting with simplelogic gates and building up the levels of abstraction until onecan create games like Tetris. There is no specific programminglanguage requirement, but some experience with programming isneeded. Prerequisite: CSE 247.Credit 3 units. EN: BME T, TU

E81 CSE 400 Independent StudyInvestigation of a topic in computer science and engineering ofmutual interest to the student and a mentor. Interested studentsare encouraged to approach and engage faculty to develop atopic of interest. A form (https://cse.wustl.edu/undergraduate/PublishingImages/Pages/undergraduate-research/Independent%20Study%20Form%20400.pdf) declaring the agreement mustbe filed in the departmental office. This course carries universitycredit, but it does not count toward a CSE major or minor. Toarrange for CSE major or minor credit for independent study, astudent must enroll in CSE 400E instead of CSE 400. Consultalso: CSE 400E.Credit variable, maximum 6 units.

E81 CSE 400E Independent StudyInvestigation of a topic in computer science and engineeringof mutual interest to the student and a mentor. Interestedstudents are encouraged to approach and engage faculty todevelop a topic of interest. A form declaring the agreement(https://cse.wustl.edu/undergraduate/PublishingImages/Pages/undergraduate-research/Independent%20Study%20Form%20400.pdf) must be filed in the departmental office. Creditearned for CSE 400E can be counted toward a student's majoror minor program, with the consent of the student's advisor.Consult also: CSE 400.Credit variable, maximum 6 units.

E81 CSE 411A AI and SocietyAI has made increasing inroads in a broad array of applications,many that have socially significant implications. This course willstudy a number of such applications, focusing on issues suchas AI used for social good, fairness and accountability of AI, andpotential security implications of AI systems. Prerequisite: CSE247.Credit 3 units. EN: TU

E81 CSE 416A Analysis of Network DataThis course examines complex systems through the eyes ofa computer scientist. We will use the representative power ofgraphs to model networks of social, technological, or biologicalinteractions. Network analysis provides many computational,algorithmic, and modeling challenges. We begin by studyinggraph theory, allowing us to quantify the structure and

interactions of social and other networks. We will then explorehow to practically analyze network data and how to reasonabout it through mathematical models of network structure andevolution. We will also investigate algorithms that extract basicproperties of networks in order to find communities and infernode properties. Finally, we will study a range of applicationsincluding robustness and fragility of networks such as theinternet, spreading processes used to study epidemiology or viralmarketing, and the ranking of webpages based on the structureof the webgraph. This course combines concepts from computerscience and applied mathematics to study networked systemsusing data mining. Prerequisites: CSE 247, ESE 326, MATH309, and programming experience. (Note: We will parse dataand analyze networks using Python.)Credit 3 units. EN: BME T, TU

E81 CSE 417T Introduction to Machine LearningThe field of machine learning is concerned with the question ofhow to construct computer programs that automatically improvewith experience. This course is a broad introduction to machinelearning, covering the foundations of supervised learning andimportant supervised learning algorithms. Topics to be coveredare the theory of generalization (including VC-dimension, thebias-variance tradeoff, validation, and regularization) and linearand non-linear learning models (including linear and logisticregression, decision trees, ensemble methods, neural networks,nearest-neighbor methods, and support vector machines).Prerequisites: CSE 247, ESE 326 (or Math 3200), Math 233, andMath 309 (can be taken concurrently).Credit 3 units. EN: BME T, TU

E81 CSE 422S Operating Systems OrganizationThis course involves a hands-on exploration of core OSabstractions, mechanisms and policies in the context of theLinux kernel. Readings, lecture material, studio exercises, andlab assignments are closely integrated in an active-learningenvironment in which students gain experience and proficiencywriting OS code, as well as tracing and evaluating OS operationsvia user-level programs and kernel-level monitoring tools.Topics include: system calls, interrupt handling, kernel modules,concurrency and synchronization, proportional and priority-basedscheduling of processes and threads, I/O facilities, memorymanagement, virtual memory, device management, and filesystem organization. Prerequisite: CSE 361S.Credit 3 units. EN: BME T, TU

E81 CSE 425S Programming Systems and LanguagesA systematic study of the principles, concepts and mechanismsof computer programming languages: their syntax, semanticsand pragmatics; the processing and interpretation of computerprograms; programming paradigms; and language design.Illustrative examples are selected from a variety of programminglanguage paradigms. Prerequisites: CSE 332S.Credit 3 units. EN: BME T, TU

E81 CSE 427S Cloud Computing with Big Data ApplicationsThis course provides a comprehensive introduction to appliedparallel computing using the MapReduce programming modelfacilitating large-scale data management and processing. Therewill be an emphasis on hands-on experience working with theHadoop architecture, an open-source software framework writtenin Java for distributed storage and processing of very large datasets on computer clusters. Further, we will make use of related

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big data technologies from the Hadoop ecosystem of tools, suchas Hive, Impala, and Pig in developing analytics and solvingproblems faced by enterprises today. Prerequisites: CSE 131,CSE 247, and CSE 330.Credit 3 units. EN: BME T, TU

E81 CSE 431S Translation of Computer LanguagesThe theory of language recognition and translation is introducedin support of compiler construction for modern programminglanguages. Topics include syntactic and semantic analysis,symbol table management, code generation, and runtimelibraries. A variety of parsing methods is covered, includingtop-down and bottom-up. Machine problems culminate in thecourse project, for which students construct a working compiler.Prerequisites: CSE 240 and CSE 247.Credit 3 units. EN: BME T, TU

E81 CSE 433R Seminar: Capture The Flag (CTF) StudioThis course provides a collaborative studio space for hands-on practice solving security-relevant puzzles in "Capture TheFlag" (CTF) format. Students will engage CTF challengesindividually and in teams, and online CTF resources requiring(free) account signup may be used. Students will be encouragedto attempt challenges commensurate with their ability, butno prior CTF experience or security knowledge is assumed.The goal of the course is to build skills in the fundamentalsof security analysis, including usage of the Linux commandline and console-based security tools, creativity in applyingtheoretical knowledge to practical challenges, and confidence inapproaching under-specified problems. Prerequisite/corequisite:CSE 433S or equivalent.Credit 1 unit.

E81 CSE 433S Introduction to Computer SecuritySecure computing requires the secure design, implementation,and use of systems and algorithms across many areas ofcomputer science. Fundamentals of secure computing suchas trust models and cryptography will lay the groundwork forstudying key topics in the security of systems, networking,web design, machine learning algorithms, mobile applications,and physical devices. Human factors, privacy, and the law willalso be considered. Hands-on practice exploring vulnerabilitiesand defenses using Linux, C, and Python in studios and labassignments is a key component of the course. Prerequisites:CSE 247 and either CSE 361 or CSE 332.Credit 3 units. EN: TU

E81 CSE 434S Reverse Engineering and Malware AnalysisThis course will focus on reverse engineering and malwareanalysis techniques. Reverse engineering -- the process ofdeconstructing an object to reveal its design and architecture-- is an essential skill in the information security community.Although hackers often use reverse engineering tools to discoverand exploit vulnerabilities, security analysts and researchersmust use reverse engineering techniques to find what a specificmalware does, how it does it, and how it got into the system. Inthis course, we will explore reverse engineering techniques andtools, focusing on malware analysis. Students will use and writesoftware during in-class studios and homework assignments toillustrate mastery of the material. Prerequisite: CSE 361S.Credit 3 units. EN: TU

E81 CSE 437R Technical InterviewingStudents will study, give, and receive technical interviews inthis seminar course. The focus will be on improving studentperformance in a technical interview setting, with the goal ofmaking our students as comfortable and agile as possible withtechnical interviews. Professionals from the local and extendedWashington University community will mentor the students in thisseminar.Credit 2 units.

E81 CSE 437S Software Engineering WorkshopAn introduction and exploration of concepts and issuesrelated to large-scale software systems development. Areasof exploration include technical complexities, organizationissues, and communication techniques for large-scaledevelopment. Students participate through teams emulatingindustrial development. The projects cover the principalsystem development life-cycle phases from requirementsanalysis, to software design, and to final implementation. Issuesrelating to real-time control systems, human factors, reliability,performance, operating costs, maintainability and others areaddressed and resolved in a reasonable manner. Prerequisite:junior or senior standing.Credit 3 units. EN: BME T, TU

E81 CSE 438S Mobile Application DevelopmentLearn how to create iOS apps in the Swift programminglanguage. This course covers a variety of topics in thedevelopment of modern mobile applications, with a focus onhands-on projects. Students will create multiple fully-functionalapps from scratch. The course emphasizes object-orienteddesign patterns and real-world development techniques. Timeis provided at the end of the course for students to work on aproject of their own interest. Prerequisite: CSE 247.Credit 3 units. EN: BME T, TU

E81 CSE 439S Mobile Application Development IIIn this course, students will work in groups to design, develop,test, publish, and market an iOS mobile application. Throughoutthe semester, students will operate in different roles on ateam, serving as lead developer, tester, and project manager.Topics include how to publish a mobile application on an appstore, APIs and tools for testing and debugging, and popularcloud-based SDKs used by developers. This course requirescompletion of the iOS version of CSE 438 Mobile ApplicationDevelopment or the appropriate background knowledge of theiOS platform.Credit 3 units. EN: TU

E81 CSE 442T Introduction to CryptographyThis course is an introduction to modern cryptography, with anemphasis on its theoretical foundations. Topics will include one-way functions, pseudorandom generators, public key encryption,digital signatures, and zero-knowledge proofs. Prerequisites:CSE 240 and CSE 247.Credit 3 units. EN: TU

E81 CSE 450A Video Game ProgrammingThis course teaches the core aspects of a video gamedeveloper's toolkit. Students work in groups and with a largegame software engine to create and playtest a full-featuredvideo game. Students will explore topics around the design

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of games through analysis of current games. Students havethe opportunity to explore additional topics including graphics,artificial intelligence, networking, physics, and user interfacedesign through their game project. Prerequisite: CSE247.Credit 3 units. EN: BME T, TU

E81 CSE 451A Video Game Programming IIThis course is a continuation of CSE 450A Video GameProgramming I. Students will work in groups and with a largegame software engine to make a full-featured video game.Students will have the opportunity to work on topics in graphics,artificial intelligence, networking, physics, user interface design,and other topics. Prerequisites: CSE 450A and permission ofinstructor.Credit 3 units. EN: TU

E81 CSE 452A Computer GraphicsIntroduction to computer graphics. The course coversfundamental concepts, data structures and algorithmsrelated to the construction, display and manipulation of three-dimensional objects. Topics include scan-conversion, basicimage processing, transformations, scene graphs, cameraprojections, local and global rendering, fractals, and parametriccurves and surfaces. Students develop interactive graphicsprograms using C++ language. Prerequisites: CSE 332S andMath 309.Credit 3 units. EN: BME T, TU

E81 CSE 457A Introduction to VisualizationDisciplines such as medicine, business, science, andgovernment are producing enormous amounts of data withincreasing volume and complexity. In this course, students willstudy the principles for transforming abstract data into usefulinformation visualizations. They will learn about the state ofthe art in visualization research and development and gainhands-on experience with designing and developing interactivevisualization tools for the web. They will also also learn howto critique existing visualizations and how to evaluate thesystems they build. Topics include design, data mapping, visualperception, and interaction. Prerequisite: CSE 330S.Credit 3 units. EN: TU

E81 CSE 460T Switching TheoryAdvanced topics in switching theory as employed in thesynthesis, analysis and design of information processingsystems. Combinational techniques: minimization, multipleoutput networks, state identification and fault detection,hazards, testability and design for test are examined. Sequentialtechniques: synchronous circuits, machine minimization, optimalstate assignment, asynchronous circuits, and built-in self-testtechniques. Prerequisite: CSE 260M.Credit 3 units. EN: BME T, TU

E81 CSE 462M Computer Systems DesignIntroduction to modern design practices, including FPGA andPCB design methodologies. Student teams use Xilinx Vivadofor HDL-based FPGA design and simulation; they also performschematic capture, PCB layout, fabrication, and testing ofthe hardware portion of a selected computation system. Thesoftware portion of the project uses Microsoft Visual Studio to

develop a user interface and any additional support softwarerequired to demonstrate final projects to the faculty during finalsweek. Prerequisites: CSE 361S and 362M from WashingtonUniversity in St. Louis or permission of the instructor.Credit 3 units. EN: TU

E81 CSE 465M Digital Systems LaboratoryHardware/software co-design; processor interfacing; proceduresfor reliable digital design, both combinational and sequential;understanding manufacturers' specifications; use of testequipment. Several single-period laboratory exercises,several design projects, and application of microprocessors indigital design. One lecture and one laboratory period a week.Prerequisites: ESE 260.Same as E35 ESE 465Credit 3 units. EN: BME T, TU

E81 CSE 467S Embedded Computing SystemsThis course introduces the issues, challenges, and methods fordesigning embedded computing systems -- systems designedto serve a particular application and which incorporate the useof digital processing devices. Examples of embedded systemsinclude PDAs, cellular phones, appliances, game consoles,automobiles, and iPods. Emphasis is given to aspects of designthat are distinct to embedded systems. The course examineshardware, software, and system-level design. Hardware topicsinclude microcontrollers, digital signal processors, memoryhierarchy, and I/O. Software issues include languages, run-timeenvironments, and program analysis. System-level topics includereal-time operating systems, scheduling, power management,and wireless sensor networks. Students will perform a courseproject on a real wireless sensor network testbed. Prerequisite:CSE 361S.Credit 3 units. EN: TU

E81 CSE 468T Introduction to Quantum ComputingThis course introduces students to quantum computing, whichleverages the effects of quantum-mechanical phenomenato solve problems. The course begins with material fromphysics that demonstrates the presence of quantum effects.Mathematical abstractions of quantum gates are studied withthe goal of developing the skills needed to reason about existingquantum circuits and to develop new quantum circuits asrequired to solve problems. Students will develop a quantum-computer simulator and make use of open simulators as well asactual devices that can realize quantum circuits on the internet.Prerequisites: CSE247, Math 309, and either Math 3200 or ESE326.Credit 3 units. EN: TU

E81 CSE 469S Security of the Internet of Things andEmbedded System SecurityThis course presents a deep dive into the emerging world of the"internet of things" from a cybersecurity perspective. With billionsof internet-enabled devices projected to impact every nook andcranny of modern existence, the concomitant security challengeportends to become dazzlingly complex. Students will learn thefundamentals of internet of things architecture and operationsfrom a layered perspective and focus on identifying, assessing,and mitigating the threats and vulnerabilities therein. Througha blend of lecture and hands-on studios, students will gain

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proficiency in the range of approaches, methods, and techniquesrequired to address embedded systems security and secure theinternet of things using actual devices from both hardware andsoftware perspectives and across a range of applications.Credit 3 units. EN: TU

E81 CSE 473S Introduction to Computer NetworksA broad overview of computer networking. Topics includehistory, protocols, Hyper Text Transfer Protocol (HTTP), FileTransfer Protocol (FTP), Simple Mail Transfer Protocol (SMTP),Domain Name System (DNS), peer-to-peer (P2P), transportlayer design issues, transport layer protocols, TransmissionControl Protocol (TCP), User Datagram Protocol (UDP), TCPcongestion control, network layer, Internet Protocol version4 (IPv4), Internet Control Message Protocol (ICMP), InternetProtocol version 6 (IPv6), routing algorithms, routing protocols,Open Shortest Path First (OSPF), Routing Information Protocol(RIP), Border Gateway Protocol (BGP), datalink layer andlocal area networks carrier sense multiple access with collisiondetection (CSMA/CD), Ethernet, virtual local area networks(VLANs), Point-to-Point Protocol (PPP), Multi-Protocol LabelSwitching, wireless and mobile networks, multimedia networking,security in computer networks, cryptography, and networkmanagement. Prerequisite: CSE 247; CSE 132 is suggested butnot required.Credit 3 units. EN: BME T, TU

E81 CSE 497 Senior Project IImplementation of a substantive project on an individualbasis, involving one or more major areas in computer science.Problems pursued under this framework may be predominantlyanalytical, involving the exploration and extension of theoreticalstructures, or they may pivot around the design/development ofsolutions for particular applications drawn from areas throughoutthe University and/or the community. In either case, the projectserves as a focal point for crystallizing the concepts, techniques,and methodologies encountered throughout the curriculum.Students intending to take CSE 497-498 must submit a projectproposal form (PDF) (https://cse.wustl.edu/undergraduate/PublishingImages/Pages/undergraduate-research/Independent%20Study%20Form%20400.pdf) for approval by the departmentduring the spring semester of the junior year. Prerequisite: seniorstanding.Credit 3 units.

E81 CSE 498 Senior Project IIImplementation of a substantive project on an individualbasis, involving one or more major areas in computer science.Problems pursued under this framework may be predominantlyanalytical, involving the exploration and extension of theoreticalstructures, or they may pivot around the design/development ofsolutions for particular applications drawn from areas throughoutthe University and/or the community. In either case, the projectserves as a focal point for crystallizing the concepts, techniques,and methodologies encountered throughout the curriculum.Students intending to take CSE 497-498 must submit a projectproposal form (PDF) (https://cse.wustl.edu/undergraduate/PublishingImages/Pages/undergraduate-research/Independent%20Study%20Form%20400.pdf) for approval by the departmentduring the spring semester of the junior year. Prerequisite: seniorstanding.Credit 3 units.

E81 CSE 499 Undergraduate Honors ThesisWorking closely with a faculty member, the student investigatesan original idea (algorithm, model technique, etc.), includinga study of its possible implications, its potential applicationand its relationship to previous related work reported in theliterature. Contributions and results from this investigation aresynthesized and compiled into a publication-quality researchpaper presenting the new idea. Prerequisites: a strong academicrecord and permission of instructor.Credit 3 units.

E81 CSE 500 Independent StudyProposal form can be located at https://cse.wustl.edu/undergraduate/PublishingImages/Pages/undergraduate-research/Independent%20Study%20Form%20400.pdfCredit variable, maximum 3 units.

E81 CSE 501N Introduction to Computer ScienceAn introduction to software concepts and implementation,emphasizing problem solving through abstraction anddecomposition. Introduces processes and algorithms, proceduralabstraction, data abstraction, encapsulation, and object-oriented programming. Recursion, iteration, and simple datastructures are covered. Concepts and skills are masteredthrough programming projects, many of which employ graphicsto enhance conceptual understanding. Java, an object-orientedprogramming language, is the vehicle of exploration. Active-learning sessions are conducted in a studio setting in whichstudents interact with each other and the professor to solveproblems collaboratively. Prerequisites: Comfort with algebraand geometry at the high school level is assumed. Patience,good planning, and organization will promote success. Thiscourse assumes no prior experience with programming.Same as E81 CSE 131Credit 3 units. BU: SCI EN: TU

E81 CSE 502N Data Structures and AlgorithmsThis course involves the study of fundamental algorithms, datastructures, and their effective use in a variety of applications.It emphasizes the importance of data structure choice andimplementation for obtaining the most efficient algorithm forsolving a given problem. A key component of this course isworst-case asymptotic analysis, which provides a quick andsimple method for determining the scalability and effectivenessof an algorithm. Prerequisite: CSE 131 and fluency withsummations, derivatives, and proofs by induction.Same as E81 CSE 247Credit 3 units. EN: TU

E81 CSE 503S Rapid Prototype Development and CreativeProgrammingThis course uses web development as a vehicle for developingskills in rapid prototyping. Students acquire the skills to build aLinux web server in Apache, to write a website from scratch inPHP, to run an SQL database, to perform scripting in Python, toemploy various web frameworks, and to develop modern webapplications in client-side and server-side JavaScript. The courseculminates with a creative project in which students are able tosynthesize the course material into a project of their own interest.The course implements an interactive studio format: after theformal presentation of a topic, students develop a related projectunder the supervision of the instructor. Prerequisite: CSE 131.Same as E81 CSE 330S

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Credit 3 units. EN: BME T, TU

E81 CSE 504N Object-Oriented Software DevelopmentLaboratoryIntensive focus on practical aspects of designing, implementingand debugging software, using object-oriented, procedural,and generic programming techniques. The course emphasizesfamiliarity and proficiency with a wide range of C++ languagefeatures through hands-on practice completing studio exercisesand lab assignments, supplemented with readings and summarypresentations for each session. Prerequisites: CSE 131 and CSE247Same as E81 CSE 332SCredit 3 units. EN: BME T, TU

E81 CSE 505N Introduction to Digital Logic and ComputerDesignIntroduction to design methods for digital logic and fundamentalsof computer architecture. Boolean algebra and logic minimizationtechniques; sources of delay in combinational circuits andeffect on circuit performance; survey of common combinationalcircuit components; sequential circuit design and analysis;timing analysis of sequential circuits; use of computer-aideddesign tools for digital logic design (schematic capture,hardware description languages, simulation); design of simpleprocessors and memory subsystems; program execution insimple processors; basic techniques for enhancing processorperformance; configurable logic devices. Prerequisite: CSE 131.Same as E81 CSE 260MCredit 3 units. EN: TU

E81 CSE 507A Technology EntrepreneurshipThis is a course for students who plan to be or to work withentrepreneurs. An entrepreneurial mindset is needed to create orgrow economically viable enterprises, be they new companies,new groups within companies, or new university laboratories.This course aims to cultivate an entrepreneurial perspective,with particular emphasis on information technology (IT)-relatedactivities. The course is jointly offered for business and CSEstudents, allowing for acculturation between these disciplines. Inaddition to an introductory treatment of business and technologyfundamentals, course topics will include business ethics,opportunity assessment, team formation, financing, intellectualproperty, and technology transfer. The course will featuresignificant participant and guest instruction from experiencedpractitioners.Credit 3 units.

E81 CSE 511A Introduction to Artificial IntelligenceThe discipline of artificial intelligence (AI) is concerned withbuilding systems that think and act like humans or rationallyon some absolute scale. This course is an introduction to thefield, with special emphasis on sound modern methods. Thetopics include knowledge representation, problem solvingvia search, game playing, logical and probabilistic reasoning,planning, dynamic programming, and reinforcement learning.Programming exercises concretize the key methods. The coursetargets graduate students and advanced undergraduates.Evaluation is based on written and programming assignments,a midterm exam and a final exam. Prerequisites: CSE 247, ESE326, Math 233.Credit 3 units. EN: TU

E81 CSE 513T Theory of Artificial Intelligence and MachineLearningMathematical foundations for Artificial Intelligence and MachineLearning. An introduction to the PAC-Semantics ("ProbablyApproximately Correct") as a common semantics for knowledgeobtained from learning and declarative sources, and thecomputational problems underlying the acquisition andprocessing of such knowledge. We emphasize the design andanalysis of efficient algorithms for these problems, and examinefor which representations these problems are known or believedto be tractable. Prerequisite: CSE 347.Credit 3 units. EN: BME T, TU

E81 CSE 514A Data MiningWith the vast advancement in science and technology, dataacquisition in large quantities are routinely done in many fields.Examples of large data include various types of data on theinternet, high-throughput sequencing data in biology andmedicine, extraterrestrial data from telescopes in astronomy,and images from surveillance camera in security. Mining alarge amount of data through data mining has become aneffective means to extracting knowledge from data. This courseintroduces the basic concepts and methods for data mining andprovides hands-on experience for processing, analyzing andmodeling structured and unstructured data. Homework problems,examines and programming assignments will be administratedthroughout the course to enhance the learning. Prerequisites:CSE 247, ESE 326 (or Math 3200), Math 233Credit 3 units. EN: BME T, TU

E81 CSE 515T Bayesian Methods in Machine LearningThis course will cover machine learning from a Bayesianprobabilistic perspective. Bayesian probability allows us tomodel and reason about all types of uncertainty. The result is apowerful, consistent framework for approaching many problemsthat arise in machine learning, including parameter estimation,model comparison, and decision making. We will begin witha high-level introduction to Bayesian inference, then proceedto cover more-advanced topics. These will include inferencetechniques (exact, MAP, sampling methods, the Laplaceapproximation, etc.), Bayesian decision theory, Bayesianmodel comparison, Bayesian nonparametrics, and Bayesianoptimization. Prerequisites: CSE 417T, ESE 326Credit 3 units. EN: BME T, TU

E81 CSE 516A Multi-Agent SystemsThis course introduces the fundamental techniques andconcepts needed to study multi-agent systems, in which multipleautonomous entities with different information sets and goalsinteract. We will study algorithmic, mathematical, and game-theoretic foundations, and how these foundations can help usunderstand and design systems ranging from robot teams toonline markets to social computing platforms. Topics coveredmay include game theory, distributed optimization, multi-agent learning and decision-making, preference elicitationand aggregation, mechanism design, and incentives in socialcomputing systems. Prerequisites: CSE 347 (may be takenconcurrently), ESE 326 (or Math 3200), and Math 233 orequivalents. Some prior exposure to artificial intelligence,machine learning, game theory, and microeconomics may behelpful, but is not required.Credit 3 units. EN: BME T, TU

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E81 CSE 517A Machine LearningThis course assumes a basic understanding of machinelearning and covers advanced topics at the frontier of thefield in-depth. Topics to be covered include kernel methods(support vector machines, Gaussian processes), neural networks(deep learning), and unsupervised learning. Depending ondevelopments in the field, the course will also cover someadvanced topics, which may include learning from structureddata, active learning, and practical machine learning (featureselection, dimensionality reduction). Prerequisites: CSE 417T.Credit 3 units. EN: TU

E81 CSE 518A Human-in-the-Loop ComputationThis course is an exploration of the opportunities and challengesof human-in-the-loop computation, an emerging field thatexamines how humans and computers can work together tosolve problems neither can yet solve alone. We will exploreways in which techniques from machine learning, game theory,optimization, online behavioral social science, and human-computer interactions can be used to model and analyze human-in-the-loop systems such as crowdsourcing markets, predictionmarkets, and user-generated content platforms. We will also lookinto recent developments in the interactions between humansand AIs, such as learning with the presence of strategic behaviorand ethical issues in AI systems. Prerequisites: CSE 247, ESE326, Math 233, and Math 309.Credit 3 units. EN: TU

E81 CSE 519T Advanced Machine LearningThis course provides a close look at advanced machine learningalgorithms -- their theoretical guarantees (computational learningtheory) and tricks to make them work in practice. In addition,this course focuses on more specialized learning settings,including unsupervised learning, semi-supervised learning,domain adaptation, multi-task learning, structured prediction,metric learning and learning of data representations. Learningapproaches may include graphical models, non-parametricBayesian statistics, and technical topics such as sampling,approximate inference and non-linear function optimization.Mathematical maturity and general familiarity of machinelearning is required. Prerequisites: CSE 511A, CSE 517A, andCSE 571ACredit 3 units. EN: TU

E81 CSE 520S Real-Time SystemsThis course covers software systems and network technologiesfor real-time applications such as automobiles, avionics,industrial automation and Internet of Things. Topics include real-time scheduling, real-time operating systems and middleware,Quality of Service, industrial networks and real-time cloudcomputing. Prerequisite: CSE 361SCredit 3 units. EN: BME T, TU

E81 CSE 521S Wireless Sensor NetworksDense collections of smart sensors networked to form self-configuring pervasive computing systems provide a basis fora new computing paradigm that challenges many classicalapproaches to distributed computing. Naming, wirelessnetworking protocols, data management, and approaches todependability, real-time, security, and middleware servicesall fundamentally change when confronted with this newenvironment. Embedded sensor networks and pervasivecomputing are among the most exciting research areas withmany open research questions. This class will study a large

number of research papers that deal with various aspects ofwireless sensor networks. Students will perform a project ona real wireless sensor network comprised of tiny devices eachconsisted of sensors, a radio transceiver, and a microcontroller.Prerequisites: CSE 361S.Credit 3 units. EN: BME T, TU

E81 CSE 522S Advanced Operating SystemsThis course offers an in-depth hands-on exploration of coreOS abstractions, mechanisms and policies, with an increasingfocus on understanding and evaluating their behaviors andinteractions. Readings, lecture material, studio exercises, andlab assignments are closely integrated in an active-learningenvironment in which students gain experience and proficiencywriting, tracing, and evaluating user-space and kernel-spacecode. Topics include: inter-process communication, real-time systems, memory forensics, file-system forensics, timingforensics, process and thread forensics, hypervisor forensics,and managing internal or external causes of anomalousbehavior. Prerequisite: CSE 422S.Credit 3 units. EN: BME T, TU

E81 CSE 523S Systems SecurityThis course examines the intersection between computer designand information security. While performance and efficiency indigital systems have improved markedly in recent decades,computer security has worsened overall in this time frame. Tounderstand why, we will explore the role that design choices playin the security characteristics of modern computer and networksystems. Students will use and write software to illustratemastery of the material. Projects will include identifying securityvulnerabilities, exploiting vulnerabilities, and detecting anddefending against exploits. Prerequisite: CSE 361S.Credit 3 units. EN: BME T, TU

E81 CSE 530S Database Management SystemsA study of data models and the database management systemsthat support these data models. The design theory for databasesis developed and various tools are utilized to apply the theory.General query languages are studied and techniques forquery optimization are investigated. Integrity and securityrequirements are studied in the context of concurrent operationson a database, where the database may be distributed overone or more locations. The unique requirements for engineeringdesign databases, image databases, and long transactionsystems are analyzed. Prerequisite: CSE 247.Credit 3 units.

E81 CSE 532S Advanced Multiparadigm SoftwareDevelopmentIntensive focus on advanced design and implementation ofconcurrent and distributed system software in C++. Topicscovered include concurrency and synchronization features andsoftware architecture patterns. Prerequisites: CSE 332S orgraduate standing and strong familiarity with C++; and CSE422S.Credit 3 units. EN: BME T, TU

E81 CSE 534A Large-Scale Optimization for Data ScienceLarge-scale optimization is an essential component of moderndata science, artificial intelligence, and machine learning.This graduate-level course rigorously introduces optimizationmethods that are suitable for large-scale problems arising in

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these areas. Students will learn several algorithms suitable forboth smooth and nonsmooth optimization, including gradientmethods, proximal methods, mirror descent, Nesterov'sacceleration, ADMM, quasi-Newton methods, stochasticoptimization, variance reduction, and distributed optimization.Throughout the class, we will discuss the efficacy of thesemethods in concrete data science problems, under appropriatestatistical models. Students will be required to program in Pythonor MATLAB. Prerequisites: CSE 247, Math 309, Math 3200 orESE 326.Credit 3 units. EN: TU

E81 CSE 538T Modeling and Performance Evaluation ofComputer SystemsModern computing systems consist of multiple interconnectedcomponents that all influence performance. The focus of thiscourse is on developing modeling tools aimed at understandinghow to design and provision such systems to meet certainperformance or efficiency targets and the trade-offs involved.The course covers Markov chains and their applications tosimple queues, and it proceeds to explore more complexsystems, including server farms and how to optimize theirperformance through scheduling and task assignment policies.The course includes a brief review of the necessary probabilityand mathematical concepts. Prerequisite: ESE 326.Credit 3 units. EN: BME T, TU

E81 CSE 539S Concepts in Multicore ComputingNowadays, the vast majority of computer systems are builtusing multicore processor chips. This fundamental shift inhardware design impacts all areas of computer science - onemust write parallel programs in order to unlock the computationalpower provided by modern hardware. The goal of this courseis to study concepts in multicore computing. We will examinethe implications of the multicore hardware design, discusschallenges in writing high performance software, and studyemerging technologies relevant to developing software formulticore systems. Topics include memory hierarchy, cachecoherence protocol, memory models, scheduling, high-level parallel language models, concurrent programming(synchronization and concurrent data structures), algorithmsfor debugging parallel software, and performance analysis.Prerequisites: CSE 247 and CSE 361S.Credit 3 units. EN: BME T, TU

E81 CSE 541T Advanced AlgorithmsProvides a broad coverage of fundamental algorithm designtechniques, with a focus on developing efficient algorithms forsolving combinatorial and optimization problems. The topicscovered include the review of greedy algorithms, dynamicprogramming, NP-completeness, approximation algorithms, theuse of linear and convex programming for approximation, andonline algorithms. Throughout this course, there is an emphasison correctness proofs and the ability to apply the techniquestaught to design efficient algorithms for problems from a widevariety of application areas. Prerequisite: CSE 347.Credit 3 units. EN: BME T, TU

E81 CSE 543S Advanced Secure Software EngineeringThe aim of this course is to provide students with broaderand deeper knowledge as well as hands-on experience inunderstanding security techniques and methods needed insoftware development. Students complete an independentresearch project which will involve synthesizing multiple softwaresecurity techniques and applying them to an actual softwareprogram or system.Credit 3 units. EN: TU

E81 CSE 543T Algorithms for Nonlinear OptimizationThe course will provide an in-depth coverage of modernalgorithms for the numerical solution of multidimensionaloptimization problems. Unconstrained optimization techniquesincluding Gradient methods, Newton's methods, Quasi-Newtonmethods, and conjugate methods will be introduced. Theemphasis is on constrained optimization techniques: Lagrangetheory, Lagrangian methods, penalty methods, sequentialquadratic programming, primal-dual methods, duality theory,nondifferentiable dual methods, and decomposition methods.The course will also discuss applications in engineering systemsand use of state-of-the-art computer codes. Special topics mayinclude large-scale systems, parallel optimization, and convexoptimization. Prerequisites: Calculus I and Math 309.Credit 3 units.

E81 CSE 544A Special Topics in Artificial IntelligenceThe material for this course varies among offerings, but thiscourse generally covers advanced or specialized topics inartificial intelligence.Credit 3 units. EN: TU

E81 CSE 544T Special Topics in Computer Science TheoryThe material for this course varies among offerings, but thiscourse generally covers advanced or specialized topics incomputer science theory.Credit 3 units. EN: BME T, TU

E81 CSE 546T Computational GeometryComputational geometry is the algorithmic study of problems thatinvolve geometric shapes such as points, lines, and polygons.Such problems appear in computer graphics, vision, robotics,animation, visualization, molecular biology, and geographicinformation systems. This course covers data structures that areunique to geometric computing, such as convex hull, Voronoidiagram, Delaunay triangulation, arrangement, range searching,KD-trees, and segment trees. Also covered are algorithms forpolygon triangulation, path planning, and the art gallery problem.Prerequisite: CSE 347.Credit 3 units.

E81 CSE 547T Introduction to Formal Languages andAutomataAn introduction to the theory of computation, with emphasis onthe relationship between formal models of computation and thecomputational problems solvable by those models. Specifically,this course covers finite automata and regular languages;Turing machines and computability; and basic measures ofcomputational complexity and the corresponding complexityclasses. Prerequisites: CSE 240 and CSE 247.Credit 3 units.

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E81 CSE 549T Theory of Parallel SystemsThe course covers various aspects of parallel programmingsuch as algorithms, schedulers and systems from a theoreticalperspective. We will cover both classic and recent results inparallel computing. Topics include parallel algorithms andanalysis in the work/span model, scheduling algorithms, externalmemory algorithms and their analysis, cache-coherenceprotocols, etc. The focus will be on design and analysis.Prerequisite: CSE 247.Credit 3 units. EN: BME T, TU

E81 CSE 554A Geometric Computing for BiomedicineWith the advance of imaging technologies deployed in medicine,engineering and science, there is a rapidly increasing amountof spatial data sets (images, volumes, point clouds, etc.) thatneed to be processed, visualized, and analyzed. This coursewill focus on a number of geometry-related computing problemsthat are essential in the knowledge discovery process in variousspatial-data-driven biomedical applications. These problemsinclude visualization, segmentation, mesh construction andprocessing, shape representation and analysis. The courseconsists of lectures that cover theories and algorithms, and aseries of hands-on programming projects using real-world datacollected by various imaging techniques (CT, MRI, electroncryo-microscopy, etc.). Prerequisite: CSE332 (or proficiency inprogramming in C++ or Java or Python) and CSE247.Credit 3 units. EN: BME T, TU

E81 CSE 555A Computational PhotographyComputational Photography describes the convergence ofcomputer graphics, computer vision, and the internet withphotography. Its goal is to overcome the limitations of traditionalphotography using computational techniques to enhance theway we capture, manipulate and interact with visual media.In this course we study many interesting, recent image-basedalgorithms and implement them to the degree that is possible.Topics may include: cameras and image formation, humanvisual perception, image processing (filtering, pyramids), imageblending and compositing, image retargeting, texture synthesisand transfer, image completion/inpainting, super-resolution,deblurring, denoising, image-based lighting and rendering, highdynamic range, depth and defocus, flash/no flash photography,coded aperture photography, single/multiview reconstruction,photo quality assessment, non photorealistic rendering, modelingand synthesis using internet data, and others. Prerequisites:CSE 452A, CSE 554A, or CSE 559A.Credit 3 units. EN: BME T, TU

E81 CSE 556A Human-Computer Interaction MethodsAn introduction to user centered design processes. The coursecovers a variety of HCI techniques for use at different stages inthe software development cycle, including techniques that canbe used with and without users. Students will gain experienceusing these techniques through in-class exercises and thenapply them in greater depth through a semester long interfacedevelopment project. Students who enroll in this course areexpected to be comfortable with building user interfacesin at least one framework and be willing to learn whateverframework is most appropriate for their project. Over the courseof the semester, students will be expected to present theirinterface evaluation results through written reports and in classpresentations. Prerequisites: 3xxS or 4xxS.Credit 3 units. EN: BME T, TU

E81 CSE 557A Advanced VisualizationWe are in an era where it is possible to have all of the world'sinformation at our fingertips. However, the more informationwe can access, the more difficult it is to obtain a holistic viewof the data or to determine what's important to make decisions.Computer-based visualization systems provide the opportunityto represent large or complex data visually to aid comprehensionand cognition. In this course, we learn about the state-of-the-artin visualization research and gain hands-on experience with theresearch pipeline. We also learn how to critique existing workand how to formulate and explore sound research questions. Wewill cover advanced Visualization topics including User Modeling,Adaptation, Personalization, Perception, and Visual Analyticsfor Non-Experts. Prerequisites: CSE 457A or permission ofinstructorCredit 3 units. EN: BME T, TU

E81 CSE 559A Computer VisionThis course introduces the fundamentals of designing computervision systems: that can "look at" images and videos and reasonabout the physical objects and scenes they represent. Topicsinclude image restoration and enhancement; estimation ofcolor, shape, geometry, and motion from images; and imagesegmentation, recognition, and classification. The focus of thecourse will be on the mathematical tools and intuition underlyingalgorithms for these tasks: models for the physics and geometryof image formation, and statistical and machine learning-basedtechniques for inference. Prerequisites: Math 309 or ESE 318 orequivalent; Math 3200 or ESE 326 or equivalent; and CSE 247or equivalentCredit 3 units. EN: BME T, TU

E81 CSE 560M Computer Systems Architecture IAn exploration of the central issues in computer architecture:instruction set design, addressing and register set design, controlunit design, microprogramming, memory hierarchies (cache andmain memories, mass storage, virtual memory), pipelining, andbus organization. The course emphasizes understanding theperformance implications of design choices, using architecturemode

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