Winter 2022

Winter 2022 Course Offerings

All courses offered in Winter 2022 will be delivered in-person (unless historically offered online).

For delivery method and date and time of offer please look at the schedule of classes.

*Instructor*	*Recommended Background*	*Area*	*Number*	*Course Title*
Ali Abedi			CS 631	Data-Intensive Dist. Analytics
Noura Limam			CS 636	Intro to Networks & Distr Syst
Gregor Richards	Familiarity with parsing and compiler basics, e.g. as taught in CS 241, is expected. Basic familiarity with object oriented and functional languages, e.g. as taught in CS 246 and CS 135 respectively, is recommended.	Programming Languages	CS 642	Principles of Prog Languages
Yizhou Zhang		Programming Languages	CS 644	Compiler Construction
Joanne Atlee	Knowledge of finite-state machines (eg as used in CS 241 or ECE 351); experience with object-orientation (eg experience with OO programming languages like Java or C#); knowledge of propositional and predicate logic (eg as used in CS 245 or ECE 108)	Software Engineering	CS 645	Sotware Req Specif & Anylysis
Shane McIntosh	Experience with team collaboration tools for software development (eg Git, GitHub, Issue Tracking), data sturctures, algorithms, and basic UML diagrams	Sotware Engineering	CS 646	Software Design, Architectures
Arie Gurfinkel		Software Engineering	CS 647	Software Test/Qual Assur/Maint
TBA		Hardware and Software Systems	CS 650	Computer Architecture
Ali Abedi		Hardware and Software Systems	CS 651	Data-Intensive Distrib Comput
Martin Karsten	C/C++ programming (CS 246); operating systems (CS 350)	Hardware and Software Systems	CS 652	Real-Time Programming
Samer Al Kiswany		Hardware and Software Systems	CS 654 - 001	Distributed Systems
Samer Al Kiswany		Hardware and Software Systems	CS 654 - 002	Distributed Systems
Noura Limam		Hardware and Software Systems	CS 656 - 001	Computer Networks
Noura Limam		Hardware and Software Systems	CS 656 – 002	Computer Networks
Hans Liljestrand, Meng Xu		Hardware and Software Systems	CS 658 – 001	Computer Security and Privacy
Hans Liljestrand, Meng Xu		Hardware and Software Systems	CS 658 – 002	Computer Security and Privacy
Jeffrey Shallit		Algorithms and Complexity	CS 662	Formal Languages & Parsing
Yuying Li	Good background in linear algebra, basic statistics, and calculus, and to have taken an introduction course in numberical computing (similar to CS 370 or 371 at UW)	Scientific and Symbolic Computing	CS 676	Num Comp for Fin Modeling
Jeff Orchard	Numerical analysis, basic statistics	SciCom or AI	CS 679	Neural Networks
Ali Ayub	Pre-requisites: CM 339/CS 341 or SE 240; Computer Science students only	Computational Statistics	CS 680 – 001	Intro to Machine Learning
Ali Ayub	Pre-requisites: CM 339/CS 341 or SE 240; Computer Science students only	Computational Statistics	CS 680 – 002	Intro to Machine Learning
Bin Ma		Bioinformatics	CS 682	Comp Tech: Biol Sequence Anal
Yuri Boykov		Artificial Intelligence	CS 684	Computational Vision
Blake Paul Allen Vanberlo	Basic calculus, probability, and algorithms	Artificial Intelligence	CS 686 – 001	Intro to Artificial Intelligence
Blake Paul Allen Vanberlo	Basic calculus, porbability, and algorithms	Artificial Intelligence	CS 686 – 002	Intro to Artificial Intelligence
Eugene Zima		Scientific and Symbolic Computing	CS 687	Intro to Symbolic Computation
Gladimir Baranoski		Graphics and User Interfaces	CS 688	Intro to Computer Graphics
Prabhakar Ragde	Open	Programming Languages	CS 747	Software Verification Using Proof Assistants
Hans De Sterck		Scientific and Symbolic Computing	CS 778	Numerical Sol of PDEs
Helen Chen		Health Informatics	CS 792 - 001	Data Structures and Standards
Helen Chen		Health Informatics	CS 792 - 081	Data Structures and Standards
Raouf Boutaba	Computer Networks, Operating Systems	Hardware and Software Systems	CS 798 – 001	Network Softwarization: Principles and Foundations
Raouf Boutaba	Computer Networks, Operating Systems	Hardware and Software Systems	CS 798 – 002	Network Softwarization: Technologies and Enablers
Shai Ben-David	Prereauisite of CS 485 or CS 685; undergraduate students that have the prerequisite could participate with the instructor's permission	Computational Statistics	CS 798 - 003	Theory of Common ML Tools
J. Ian Munro	A strong undergraduate course in data structures like CS 240 is required. A more advanced algorithms course such as CS 466 is helpful but not necessary	Algorithms	CS 840	Time and Space Efficiency
Chengnian Sun	Open	Software Engineering	CS 846 – 001	Advance Topics in Software Testing and Debugging
Shane McIntosh	Open background, but a basic understanding of software release practices, inferential statistics, and machine learning will help	Software Engineering	CS 846 – 002	SW Analytics for Release Pipe
Gordon Cormack	Undergrad CS	Databases	CS 848	Information Retrieval
Florian Kerschbaum	Undergrad security course, familiarity with databases and machine learning	Artificial Intelligence, Databases	CS 858 – 001	Security & Privacy in Data Science
Diogo Barradas	Open	Hardware and Software Systems	CS 858 – 002	Internet Censorship and Surveillance
N. Asokan	Good understanding of programming in C/C++ required, prior undergraduate level courses in security (equivalent to CS 458) and operating systems (equivalent to CS 350) strongly recommended, but not mandated	Systems	CS 858 - 003	Selected Topics in Systems Security
Lap Chi Lau	Linear algebra, probability, multivariate calculus, optimization	Algorithms and Complexity	CS 860	Eigenvalues and Polynominals
Beni Yoshida, Debbie Leung, Michael Vasmer	QIC 710 / CS 768 / CO 681 or CS 467 / CO 481	Quantum Information and Computation	CS 867	Qtm Error Corr & Flt Tolerance
Pascal Poupart	Undergrad courses in machine learning, statistics and linear algebra	Computational Statistics	CS 885	Reinforcement Learning
Ming Li	Basics in deep learning, know basic biology	AI, Learning, Bioinformatics, Health Science	CS 886	Deep Learning for Biotechnology
Gladimir Baranoski	Open	Computer Graphics, Scientific Computing, Systems, HCI	CS 898 - 001	Synergy Between CS and Biology
Yuri Boykov		Artificial Intelligence	CS 898 - 002	TBA