Washington University, St. Louis Engineering

Graduate Courses

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Dept # Course Name :  [Course Description On]  Credits
CSE 500 Independent Study 3
   
CSE 501N Programming Concepts and Practice 3
  This introductory course assumes no prior programming background and is intended for graduate students who desire significant programming and program design experience within a modern programming paradigm. Exploration of the enterprise of software design, creation, maintenance, and reuse. Abstraction as a vehicle for reducing the complexity of problems. Concepts of object-oriented programming. Internet-related programming including threads. Design and implementation of nontrivial algorithms in selected application areas. Prerequisites none. Credit 3 units. No credit toward CSE graduate degree. 
CSE 502N Fundamentals of Computer Science 3
  Formerly CS 514N. This course, intended for graduate students without a computer science background, covers the core components seen in a computer science undergraduate curriculum on which our graduate level courses rely. Topics include fundamental algorithms, data structures, proof techniques, computational models, machine organization, and software design and implementation. Prerequisites: graduate standing; CSE 501N or prior programming experience; some mathematical sophistication highly desirable. No credit towards CSE graduate degree. 
CSE 504N Object-Oriented Software Development Laboratory 3
  Intensive focus on practical aspects of designing, implementing and debugging object-oriented software. Topics covered include developing, documenting, and testing representative applications using object-oriented frameworks and C++. Design and implementation are central themes to enable the construction of reusable, extensible, efficient, and maintainable software. Prerequisites: CSE 132/CS 102G and 241. No credit toward CSE graduate degree. 
CSE 511A Introduction to Artificial Intelligence 3
  The discipline of artificial intelligence (AI) is concerned with building systems that think and act like humans or rationally on some absolute scale. This course is an introduction to the field, with special emphasis on sound modern methods. The topics include knowledge representation, problem solving via search, game playing, logical and probabilistic reasoning, planning, machine learning (decision trees, neural nets, reinforcement learning, and genetic algorithms) and machine vision. Programming exercises will concretize the key methods. The course targets graduate students and advanced undergraduates. Evaluation is based on written and programming assignments, a midterm exam, and a final exam. Prerequisite: CSE 132, CSE 240, and CSE 241, or permission of the instructor. 
CSE 517A Machine Learning 3
  The field of machine learning is concerned with the question of how to construct computer programs that automatically improve with experience. Recently, many successful machine learning applications have been developed, ranging from data-mining programs that learn to detect fraudulent credit card transactions, to information-filtering systems that learn users' reading preferences, to autonomous vehicles that learn to drive. There have also been important advances in the theory and algorithms that form the foundation of this field. This course will provide a broad introduction to the field of machine learning. Prerequisites: CSE 241. 
CSE 542T Advanced Data Structures and Algorithms 3
  This course is concerned with the design and analysis of efficient algorithms, focusing principally on algorithms for combinatorial optimization problems. A key element in the course is the role of data structures in algorithm design and the use of amortized complexity analysis to determine how data structures affect performance. The course is organized around a set of core problems and algorithms, including the classical network optimization algorithms, as well as newer and more efficient algorithms. This core is supplemented by algorithms selected from the recent technical literature. Prerequisite: CSE 241. 
CSE 547T Introduction to Formal Languages and Automata 3
  An introduction to the mathematical theory of languages and grammars. Topics include deterministic and nondeterministic finite state machines, push-down automata, and Turing machines; regular, context-free and recursive languages; closure properties of languages; the concepts of computability and undecidability. Prerequisite: CSE 240. 
CSE 553S Advanced Mobile Robotics 3
  This course covers advanced topics from the theory and practice of mobile robotics. Students will read, present and discuss papers from the current research literature. There will be a substantial programming project, in which students implement and test ideas from the current research literature on one of the department's research robot platforms. Prerequisites: CSE 550A and strong programming skills (preferably in C++). 
CSE 559A Computer Vision 3
  Computer vision is the process of automatically extracting information from images and video. This course covers imaging geometry (camera calibration, stereo, and panoramic image stitching), and algorithms for video surveillance (motion detection and tracking), segmentation and object recognition. Final projects for the course will explore challenges in analysis of real-world data. Students with non-standard backgrounds (such as video art, or the use of imaging in physics and biology) are encouraged to contact the instructor. Prerequisites: CSE 241 and linear algebra. 
CSE 561M Computer Systems Architecture II 3
  Advanced techniques in computer system design. Selected topics from: processor and SoC design (multi-core organization, system-level integration), run-time systems, memory systems (topics in locality and special-purpose memories), I/O subsystems and devices, systems security, and power considerations. Prereqs: CSE 560M or permission of instructor. 3 units. Same as E71 CS 561M.  
CSE 568M Imaging Sensors 3
  This course will cover topics on digital imaging sensors including basic operations of silicon photodetectors; CCD and CMOS passive and active sensor operation; temporal and spatial noise in CMOS sensors; spatial resolution and MTF; SNR and dynamic range; high dynamic range architectures and application specific imaging sensors such as polarization imaging and fluorescent imaging sensors. 
CSE 598 Masters Project 6
  Students electing the project option for their master's degree perform their project work under this course. Prerequisite: permission of adviser. 
CSE 599 Masters Research 6
  Prerequisite: permission of adviser. 
CSE 699 Doctoral Research 9
   
CSE 7100 Research Seminar on Machine Learning 1
  This seminar will focus on recent advances in the field of machine learning. Students will read, present, discuss, and implement recent work from the research literature. Emphasis will be placed on parallel ML algorithms, time series data, multi-task and transfer learning and others. Prereqs: CSE 517A or permission of instructor. 
CSE 7200 Research Seminar on Robotics and Human-Computer Interaction 1
  This section will focus on human-computer interaction and not robotics. Human-computer interaction (HCI) blends ideas in social science with innovations in computer science to study how we relate to computational devices. This seminar examines recent HCI research contributions spanning topics such as user-centered design, useful games, software usability, interaction techniques, collaboration, visualization, social media, user experience, adaptive systems, tangible interfaces, and end-user programming. On a rotating basis participants are expected to present preselected papers covering these HCI topic areas. 
CSE 7300 Research Seminar on Software Systems 1
  Research seminars examine publications, techniques, approaches, and strategies within an area of computer science and engineering. Seminars are highly participational: students are expected to take turns presenting material, to prepare for seminar by reading any required material, and to contribute to the group's discussions. The actual topics covered in a seminar will vary by semester and instructor. Interested students are encouraged to obtain a syllabus from the instructor's web page or by contacting the instructor. Section 01 focuses on the area of wireless sensor networks and systems. Section 02 focuses on the area of real-time systems. 
CSE 7500 Research Seminar on Graphics and Vision 1
  The research on computer graphics and computer vision has advanced by leaps and bounds in recent years. In this seminar, we will explore the state-of-art in these areas by studying and critiquing papers published recently in important venues such as CVPR and Siggraph. 
CSE 7600 Research Seminar on Computer Engineering 1
  This seminar explores contemporary topics in computer engineering. Each week, the seminar will focus on a selected topic or reading from the research literature; student-led presentations will summarize important contributions and guide the discussion. Particular emphasis will be placed on future research directions and opportunities. Section 01 will focus on computer systems architecture; section 02 will focus on polarization imaging. 
CSE 7700 Research Seminar on Networking and Communications 1
  In this research seminar we study the design of modern data networks, concentrating on new and emerging research topics. Broad topics of interest include router design, packet scheduling, network control, multimedia applications, extensible networking and optical switching. Participants are expected to present recent papers on research topics of current interest and/or present results from their own research activities. 
CSE 7800 Research Seminar in Computational and Systems Biology 1
  This seminar focuses on papers from the recent literature in computational biology, bioinformatics, and systems biology. Students read, present, and discuss recent works of interest in areas such as comparative genomics, proteomics, gene regulation, motif finding, and network reconstruction and modeling. Paper selection emphasizes new computational approaches and analysis of results from high-throughput experimental technologies.  
CSE 883 Masters Continuing Student Status 0
   
CSE 884 Doctoral Continuing Student Status 0
   
CSE 885 Masters Nonresident 0
   
CSE 886 Doctoral Nonresident 0
   

Washington University in St. Louis School of Engineering & Applied Science, Department of Computer Science & Engineering

Bryan Hall, CB 1045, 1 Brookings Drive, Saint Louis, MO, USA 63130
Phone: (314) 935-6160, Fax: (314) 935-7302

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