The Department of Computer Science & Engineering (CSE) offers an array of courses that can be taken as requirements or electives for any of the undergraduate degree programs. Students will explore topics around the design of games through analysis of current games. Topics covered may include game theory, distributed optimization, multi-agent learning and decision-making, preference elicitation and aggregation, mechanism design, and incentives in social computing systems. Prerequisite: CSE 361S. CS+Business:This joint majorprovides students with the fundamental knowledge and perspectives of computer science and business and of the unique opportunities created by combining them. Prerequisites: CSE 450A and permission of instructor. We will study algorithmic, mathematical, and game-theoretic foundations, and how these foundations can help us understand and design systems ranging from robot teams to online markets to social computing platforms. Website: heming-zhang.github.io Email: hemingzhang@wustl.edu EDUCATION Washington University in St.Louis, St.Louis, MO August 2019 - Present McKelvey School of Engineering Master of Science, Computer Science Major GPA: 4.0/4.0 Central China Normal University, Wuhan, China September 2015 - June 2019 School of Information Management Bachelor . This course presents a deep dive into the emerging world of the "internet of things" from a cybersecurity perspective. The discipline of artificial intelligence (AI) is concerned with building systems that think and act like humans or rationally on some absolute scale. (CSE 332S) Washington University McKelvey School of Engineering Aug 2020 - . Create a new C++ Console Application within your repository, make sure to name it something descriptive such as Lab3. An introduction and exploration of concepts and issues related to large-scale software systems development. For more information about these programs, please visit the McKelvey School of Engineering website. E81CSE473S Introduction to Computer Networks. Computer-based visualization systems provide the opportunity to represent large or complex data visually to aid comprehension and cognition. E81CSE412A Introduction to Artificial Intelligence. We will also look into recent developments in the interactions between humans and AIs, such as learning with the presence of strategic behavior and ethical issues in AI systems. Analyzing a large amount of data through data mining has become an effective means of extracting knowledge from data. You signed out in another tab or window. This course provides an overview of practical implementation skills. Co-op: The Cooperative Education Program allows a student to get valuable experience working in industry while an undergraduate. Prerequisites: CSE 131. This course is an introduction to modern cryptography, with an emphasis on its theoretical foundations. Enter the email address you signed up with and we'll email you a reset link. Communes of the Ille-et-Vilaine department, "Rpertoire national des lus: les maires", The National Institute of Statistics and Economic Studies, https://en.wikipedia.org/w/index.php?title=Acign&oldid=1101112472, Short description is different from Wikidata, Pages using infobox settlement with image map1 but not image map, Articles with French-language sources (fr), Creative Commons Attribution-ShareAlike License 3.0, This page was last edited on 29 July 2022, at 10:57. Most applications courses provide background not only in the applications themselves but also in how the applications are designed and implemented. For more information, contact the department office by email at admissions@cse.wustl.edu or by phone at 314-935-6132. See also CSE 400. Boolean algebra and logic minimization techniques; sources of delay in combinational circuits and effect on circuit performance; survey of common combinational circuit components; sequential circuit design and analysis; timing analysis of sequential circuits; use of computer-aided design tools for digital logic design (schematic capture, hardware description languages, simulation); design of simple processors and memory subsystems; program execution in simple processors; basic techniques for enhancing processor performance; configurable logic devices. This course provides a collaborative studio space for hands-on practice solving security-relevant puzzles in "Capture The Flag" (CTF) format. Prerequisites: CSE 247 and either CSE 361 or CSE 332. This course examines the intersection between computer design and information security. E81CSE433R Seminar: Capture The Flag (CTF) Studio. However, students must also cultivate curiosity about data, including the data's provenance, ethical considerations such as bias, and skepticism concerning correlation and causality. Please make sure to have a school email added to your github account before signing in! GitHub - anupamguptacal/cse332-p2-goldenaxe anupamguptacal / cse332-p2-goldenaxe Public Star master 1 branch 0 tags Code 75 commits Failed to load latest commit information. Upon request, the computer science department will evaluate a student for proficiency for any of our introductory courses. Topics include memory hierarchy, cache coherence protocol, memory models, scheduling, high-level parallel language models, concurrent programming (synchronization and concurrent data structures), algorithms for debugging parallel software, and performance analysis. Centre Commercial Des Lonchamps. The projects cover the principal system development life-cycle phases from requirements analysis, to software design, and to final implementation. Prerequisite: CSE 361S. Such an algorithm is known as an approximation algorithm. Questions should be directed to the associate chair at associatechair@cse.wustl.edu. The course emphasizes familiarity and proficiency with a wide range of C++ language features through hands-on practice completing studio exercises and lab assignments, supplemented with readings and summary presentations for each session. 2022 Washington University in St.Louis, Barbara J. This course is a survey of algorithms and mathematical methods in biological sequence analysis (with a strong emphasis on probabilistic methods) and systems biology. Students intending to take CSE 497-498 must submit a project proposal form (PDF) for approval by the department during the spring semester of the junior year. sauravhathi folder created and org all files. Systems biology topics include the discovery of gene regulatory networks, quantitative modeling of gene regulatory networks, synthetic biology, and (in some years) quantitative modeling of metabolism. The PDF will include content on the Overview tab only. 24. Additional information can be found on our CSE website, or any of the CSE faculty can offer further guidance and information about our programs. E81CSE217A Introduction to Data Science. The course is self-contained, but prior knowledge in algebra (e.g., Math 309, ESE 318), discrete math (e.g., CSE 240, Math 310), and probability (e.g., Math 2200, ESE 326), as well as some mathematical maturity, is assumed. Applicants are judged on undergraduate performance, GMAT scores, summer and/or co-op work experience, recommendations and a personal interview. Examples of large data include various types of data on the internet, high-throughput sequencing data in biology and medicine, extraterrestrial data from telescopes in astronomy, and images from surveillance cameras in security settings. cse 332 guessing gamebrick police blotter. You signed in with another tab or window. Topics include scan-conversion, basic image processing, transformations, scene graphs, camera projections, local and global rendering, fractals, and parametric curves and surfaces. A broad overview of computer networking. People are attracted to the study of computing for a variety of reasons. cse 332 guessing gamestellaris unbidden and war in heaven. Study Resources. The material for this course varies among offerings, but this course generally covers advanced or specialized topics in computer science systems. GitLab cse332-20au p3 Repository An error occurred while loading the blob controls. The students design combinational and sequential circuits at various levels of abstraction using a state-of-the-art CAD environment provided by Cadence Design Systems. We will cover advanced visualization topics including user modeling, adaptation, personalization, perception, and visual analytics for non-experts. If you have not taken either of these courses yet you should take at least one of them before taking CSE 332, especially since we will assume you have at least 2 or 3 previous semesters of programming proficiency before enrolling in this course. Students will perform a course project on a real wireless sensor network testbed. The course covers various aspects of parallel programming such as algorithms, schedulers and systems from a theoretical perspective. Prerequisite: CSE 131.Same as E81 CSE 260M, E81CSE513T Theory of Artificial Intelligence and Machine Learning. If a student's interests are concentrated in the first two areas, a computer engineering degree might be best. Courses in this area help students gain a solid understanding of how software systems are designed and implemented. Students will learn several algorithms suitable for both smooth and nonsmooth optimization, including gradient methods, proximal methods, mirror descent, Nesterov's acceleration, ADMM, quasi-Newton methods, stochastic optimization, variance reduction, and distributed optimization. CSE 142: Computer Programming I Basic programming-in-the-small abilities and concepts including procedural programming (methods, parameters, return, values), basic control structures (sequence, if/else, for loop, while loop), file processing, arrays, and an introduction to defining objects. The course material focuses on bottom-up design of digital integrated circuits, starting from CMOS transistors, CMOS inverters, combinational circuits and sequential logic designs. There is no single class that will serve as the perfect prerequisite, but certainly having a few computer science classes under your belt will be a helpful preparation. Examples include operating systems, which manage computational resources; network protocols, which are responsible for the delivery of information; programming languages, which support the construction of software systems and applications; and compilers, which translate computer programs into executable form. We will examine the implications of the multicore hardware design, discuss challenges in writing high performance software, and study emerging technologies relevant to developing software for multicore systems. A second major in computer science can expand a student's career options and enable interdisciplinary study in areas such as cognitive science, computational biology, chemistry, physics, philosophy and linguistics. Important design aspects of digital integrated circuits such as propagation delay, noise margins and power dissipation are covered in the class, and design challenges in sub-micron technology are addressed. By logging into this site you agree you are an authorized user and agree to use cookies on this site. Machine problems culminate in the course project, for which students construct a working compiler. We will explore ways 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, prediction markets, and user-generated content platforms. E81CSE365S Elements of Computing Systems. Some prior exposure to artificial intelligence, machine learning, game theory, and microeconomics may be helpful, but is not required. Each project will then provide an opportunity to explore how to apply that model in the design of a new user interface. The course emphasizes object-oriented design patterns and real-world development techniques. Open up Visual Studio 2019, connect to GitHub, and clone your newly created repository to create a local working copy on your h: drive. While performance and efficiency in digital systems have improved markedly in recent decades, computer security has worsened overall in this time frame. Concepts and skills are mastered through programming projects, many of which employ graphics to enhance conceptual understanding. The CSE332 Web: 1993-2023, Department of Computer Science and Engineering, Univerity of Washington. Students develop interactive graphics programs using C++ language. View Sections. P p2 Project ID: 53371 Star 2 92 Commits 1 Branch 0 Tags 31.8 MB Project Storage Forked from cse332-20su / p2 master p2 Find file Clone README CI/CD configuration No license. GitHub. Prerequisite: CSE 247. In addition to these six programs, CSE offers a pre-medical option and combined undergraduate/graduate programs. The aim of this course is to provide students with broader and deeper knowledge as well as hands-on experience in understanding security techniques and methods needed in software development. Prerequisites: CSE 347 (may be taken concurrently), ESE 326 (or Math 3200), and Math 233 or equivalents. Evaluation is based on written and programming assignments, a midterm exam and a final exam. The course emphasizes understanding the performance implications of design choices, using architecture modeling and evaluation using simulation techniques. Login with Github. The focus of this course is on developing modeling tools aimed at understanding how to design and provision such systems to meet certain performance or efficiency targets and the trade-offs involved. PhD Student Researcher. This seminar will host faculty, alumni, and professionals to discuss topics related to the study and practice of computer science. Emphasizes importance of data structure choice and implementation for obtaining the most efficient algorithm for solving a given problem. Many applications make substantial performance demands upon the computer systems upon which those applications are deployed. Measurement theory -- the study of the mismatch between a system's intended measure and the data it actually uses -- is covered. E81CSE587A Algorithms for Computational Biology. Emphasizes importance of data structure choice and implementation for obtaining the most efficient algorithm for solving a given problem. Prerequisites: CSE 332S and Math 309. More About Virtual Base Classes Still Polymorphic Can convert between uses as Derived vs. Base Members of virtual Base class normally can be uniquely identified base class is instantiated only once if the variable is in both base and derived class, then derived class has higher precedence If the member is in 2 derived classes, then it is still . Prerequisite: familiarity with software development in Linux preferred, graduate standing or permission of instructor. Additional reference material is available. The goal of the course is to design a microprocessor in 0.5 micron technology that will be fabricated by a semiconductor foundry. Applications are the ways in which computer technology is applied to solve problems, often in other disciplines. The breadth of computer science and engineering may be best understood in terms of the general areas of applications, software systems, hardware and theory. Find and fix vulnerabilities . E81 CSE 555A Computational Photography. Depending on developments in the field, the course will also cover some advanced topics, which may include learning from structured data, active learning, and practical machine learning (feature selection, dimensionality reduction). This is a project-oriented course on digital VLSI design. Topics covered will include various C++ language features and semantics, especially from the C++11 standard onward, with studio exercises and lab assignments designed to build proficiency in using them effectively within and across the different programming paradigms. Bachelor's/master's applications will be accepted until the last day of classes the semester prior to the student beginning the graduate program. Prerequisites: CSE 240 and CSE 247. In 1010, Rivallon, Baron of Vitr ceded the territory of Acign to his son Renaud. Learning approaches may include graphical models, non-parametric Bayesian statistics, and technical topics such as sampling, approximate inference, and non-linear function optimization. A seminar and discussion session that complements the material studied in CSE 131. Special topics may include large-scale systems, parallel optimization, and convex optimization. Examples of embedded systems include PDAs, cellular phones, appliances, game consoles, automobiles, and iPods. Students who enroll in this course are expected to be comfortable with building user interfaces in at least one framework and be willing to learn whatever framework is most appropriate for their project. The field of computer science and engineering studies the design, analysis, implementation and application of computation and computer technology. This fundamental shift in hardware design impacts all areas of computer science - one must write parallel programs in order to unlock the computational power provided by modern hardware. Problems pursued under this framework may be predominantly analytical, involving the exploration and extension of theoretical structures, or they may pivot around the design/development of solutions for particular applications drawn from areas throughout the University and/or the community. The combination of the two programs extends the flexibility of the undergraduate curriculum to more advanced studies, thereby enabling students to plan their entire spectrum of computing studies in a more comprehensive educational framework. Board game; Washington University in St. Louis CSE 332. lab2-2.pdf. To help students balance their elective courses, most upper-level departmental courses are classified into one of the following categories: S for software systems, M for machines (hardware), T for theory, or A for applications. The course implements an interactive studio format: after the formal presentation of a topic, students develop a related project under the supervision of the instructor. Enter the email address you signed up with and we'll email you a reset link. Topics include classical string matching, suffix array string indices, space-efficient string indices, rapid inexact matching by filtering (including BLAST and related tools), and alignment-free algorithms. The PDF will include content on the Minors tab only. Interested students are encouraged to approach and engage faculty to develop a topic of interest. Create a new C++ Console Application within your repository, make sure to name it something descriptive such as Lab3 . Throughout the semester, students will operate in different roles on a team, serving as lead developer, tester, and project manager. 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. The topics include common mistakes, selection of techniques and metrics, summarizing measured data, comparing systems using random data, simple linear regression models, other regression models, experimental designs, 2**k experimental designs, factorial designs with replication, fractional factorial designs, one factor experiments, two factor full factorial design w/o replications, two factor full factorial designs with replications, general full factorial designs, introduction to queueing theory, analysis of single queues, queueing networks, operational laws, mean-value analysis, time series analysis, heavy tailed distributions, self-similar processes, long-range dependence, random number generation, analysis of simulation results, and art of data presentation. Credit earned for CSE 400E can be counted toward a student's major or minor program, with the consent of the student's advisor. View CSE 332S - Syllabus.pdf from CSE 332S at Washington University in St Louis. cse332s-sp21-wustl has one repository available. Portions of the CSE473 web may be reprinted or adapted for academic nonprofit purposes, providing the source is accurately quoted and duly creditied. The PDF will include content on the Faculty tab only. Page written by Roger D. Chamberlain and James Orr. CSE 332: Data Structures and Parallelism Covers abstract data types and structures including dictionaries, balanced trees, hash tables, priority queues, and graphs; sorting; asymptotic analysis; fundamental graph algorithms including graph search, shortest path, and minimum spanning trees; concurrency and synchronization; and parallelism. Throughout the course, students present their findings in their group and to the class. A key component of this course is worst-case asymptotic analysis, which provides a quick and simple method for determining the scalability and effectiveness of an algorithm. Prerequisites: CSE 131 and CSE 132. The course targets graduate students and advanced undergraduates. E81CSE532S Advanced Multiparadigm Software Development. Prerequisite: CSE247. We . E81CSE438S Mobile Application Development. Prerequisites: CSE 332S or graduate standing and strong familiarity with C++; and CSE 422S. Required Text Topics to be covered are the theory of generalization (including VC-dimension, the bias-variance tradeoff, validation, and regularization) and linear and non-linear learning models (including linear and logistic regression, decision trees, ensemble methods, neural networks, nearest-neighbor methods, and support vector machines). CSE 132 (Computer Science II) or CSE 241 (Algorithms and Data Structures). In the Spring of 2020, all Washington University in St. Louis students were sent home. The Department of Computer Science & Engineering offers in-depth graduate study in many areas. Roch Gurin Harold B. and Adelaide G. Welge Professor of Computer Science PhD, California Institute of Technology Computer networks and communication systems, Sanjoy Baruah PhD, University of Texas at Austin Real-time and safety-critical system design, cyber-physical systems, scheduling theory, resource allocation and sharing in distributed computing environments, Aaron Bobick James M. McKelvey Professor and Dean PhD, Massachusetts Institute of Technology Computer vision, graphics, human-robot collaboration, Michael R. Brent Henry Edwin Sever Professor of Engineering PhD, Massachusetts Institute of Technology Systems biology, computational and experimental genomics, mathematical modeling, algorithms for computational biology, bioinformatics, Jeremy Buhler PhD, Washington University Computational biology, genomics, algorithms for comparing and annotating large biosequences, Roger D. Chamberlain DSc, Washington University Computer engineering, parallel computation, computer architecture, multiprocessor systems, Yixin Chen PhD, University of Illinois at Urbana-Champaign Mathematical optimization, artificial intelligence, planning and scheduling, data mining, learning data warehousing, operations research, data security, Patrick Crowley PhD, University of Washington Computer and network systems, network security, Ron K. Cytron PhD, University of Illinois at Urbana-Champaign Programming languages, middleware, real-time systems, Christopher D. Gill DSc, Washington University Parallel and distributed real-time embedded systems, cyber-physicalsystems, concurrency platforms and middleware, formal models andanalysis of concurrency and timing, Raj Jain Barbara J.
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