Graduate Programs

Spring Term Schedule

Spring 2024

Number	Title	Instructor	Time
CSC 402-1 Network Science Analysis Gonzalo Mateos Buckstein MW 3:25PM - 4:40PM
The science of networks is an emerging discipline of great importance that combines graph theory, probability and statistics, and facets of engineering and the social sciences. This course will provide students with the mathematical tools and computational training to understand large-scale networks in the current era of Big Data. It will introduce basic network models and structural descriptors, network dynamics and prediction of processes evolving on graphs, modern algorithms for topology inference, community and anomaly detection, as well as fundamentals of social network analysis. All concepts and theories will be illustrated with numerous applications and case studies from technological, social, biological, and information networks. Prerequisites: Some mathematical maturity, comfortable with linear algebra, probability, and analysis (e.g., MTH164-165). Exposure to programming and Matlab useful, but not required. For more information, please visit the class website: https://www.hajim.rochester.edu/ece/sites/gmateos/ECE442.html Location Computer Studies Room 601
CSC 404-1 Multiprocessor Arch Michael Huang WF 3:25PM - 4:40PM
This course provides in-depth discussions of the design and implementation issues of multiprocessor system architecture. Topics include cache coherence, memory consistency, interconnect, their interplay and impact on the design of high-performance micro-architectures. prerequisite ECE 200 or CSC 252 or permission of instructor. PREREQUISITES: ECE 200 or CSC 252 or permission of instructor Location Hylan Building Room 101
CSC 412-1 Human Computer Interaction Yukang Yan TR 12:30PM - 1:45PM
This course will explore the design, implementation, and evaluation of user interfaces. Students will study the theoretical methods for interface design and evaluation, including requirements gathering, usability heuristics, user interface inspections, usability studies, information visualization, and prototyping. Case studies of interface successes and failures will augment theory with practical experiences. Students will apply this methodology to assignments in the design, implementation, and evaluation cycle. Students taking this course at the graduate level will have additional readings and assignments. Location Hylan Building Room 102
CSC 414-1 Selected Topics in Augmented and Virtual Reality Mujdat Cetin; Zhiyao Duan MW 2:00PM - 3:15PM
This is the second course offered as part of the PhD training program on augmented and virtual reality. It builds on the first course, Introduction to Augmented and Virtual Reality (AR/VR). The goal of the course is to provide exposure to problems in the AR/VR domain addressed by various disciplines. The course consists of three one-month long modules in a semester. Modules engage students in particular aspects of AR/VR or hands-on experience on AR/VR. Modules to be offered in various years include: fundamentals of optics for AR/VR; AR/VR in the silicon; foundations of visual perception in the context of AR/VR; computer audition and acoustic rendering; measuring the human brain; deep learning and visual recognition for AR/VR; brain-computer interfacing in a virtual environment; 3D interfaces and interaction; AR/VR for collaborative education & professional training. In Spring 2024, the following three modules will be offered: 1) Fundamentals of optics for AR/VR. Optics is central to near-eye displays and sensing. In this module, students will learn basic concepts and terminology of optics for AR/VR, as well as key visual requirements. Students will then learn about different optical architectures based on free-space or waveguide optics. Emerging technologies enabling compact architectures such as freeform optics and meta optics will be discussed. Students will explore hands-on design in optical design software. This module will be designed by Jannick Rolland (Prof. Optics, Visual Science, and BME), whose research focuses on optical instrumentation across a wide range of applications, including AR/VR. 2) Computer audition and acoustic rendering. (Prof. Zhiyao Duan) Sound is an important medium for human interaction. Designing algorithms and systems that are capable of understanding, processing, generating, and rendering sound is a critical step toward natural human-data-system interfaces. In this module, students will learn basic concepts and gain hands-on experience on four fundamental problems in designing sound-based interfaces: sound recognition, source separation, music generation, and spatial audio rendering. 3) Professional encounters with leading AR/VR researchers. This module involves a series of seminars and discussion sessions with leading AR/VR researchers from academia and industry. Prerequisites: ECE 410 or OPT 410 or BME 410 or NSCI 415 or CSC 413 or CVSC 534 INSTRUCTORS: Jannick Rolland; Zhiyao Duan; Mujdat Cetin Location Morey Room 205
CSC 416-1 AR/VR Interaction Design Zhen Bai TR 3:25PM - 4:40PM
Human activity is embodied through all our sensorimotor capacities, immersed in our immediate physical, social & cultural surroundings. Interaction technologies such as Augmented Reality (AR) & Virtual Reality (VR) have shown vast potential to enhance the way we think, feel & behave by superimposing or substituting digital contents onto our reality. This new undergraduate course is an introduction to AR,VR & related technologies. This course helps students build a frame of reference of those technologies, apply them in design practices that address real-world problems, & actively reflect on social implications. CSC 172 and CSC 214 required (or proven equivalent application development experience); CSC 131 recommended. Location Lattimore Room 210
CSC 440-1 Data Mining Thaddeus Pawlicki TR 4:50PM - 6:05PM
Fundamental concepts and techniques of data mining, including data attributes, data visualization, data pre-processing, mining frequent patterns, association and correlation, classification methods, and cluster analysis. Advanced topics include outlier detection, stream mining, and social media data mining. CSC 440, a graduate-level course, requires additional readings and a course project. Location Dewey Room 1101
CSC 446-1 Machine Learning Jian Kang TR 11:05AM - 12:20PM
Mathematical foundations of classification, regression, and decision making. Supervised algorithms covered include perceptrons, logistic regression, support vector machines, and neural networks. Directed and undirected graphical models. Numerical parameter optimization, including gradient descent, expectation maximization, and other methods. Introduction to reinforcement learning. Proofs covered as appropriate. Significant programming projects will be assigned. This course involves a lot of math and algorithms. You should know multivariable calculus, linear algebra, and some algorithms. No formal prerequisites but MATH 165, MATH 164, and CSC 242 strongly recommended. Location Hylan Building Room 203
CSC 449-1 Machine Vision Chenliang Xu TR 9:40AM - 10:55AM
Introduction to computer vision, including camera models, basic image processing, pattern and object recognition, and elements of human vision. Specific topics include geometric issues, statistical models, Hough transforms, color theory, texture, and optic flow. CSC 449, a graduate-level course, requires additional readings and assignments. Prerequisites: MATH 161 and CSC 242; MATH 165 strongly recommended Location Gavett Hall Room 202
CSC 452-1 Computer Organization Chen Ding WF 3:25PM - 4:40PM
Introduction to computer architecture and the layering of hardware/software systems. Topics include instruction set design; logical building blocks; computer arithmetic; processor organization; the memory hierarchy (registers, caches, main memory, and secondary storage); I/Obuses, devices, and interrupts; microcode and assembly language; virtual machines; the roles of the assembler, linker, compiler, and operating system; technological trends and the future of computing hardware. Several programming assignments required. Location Gavett Hall Room 206
CSC 454-1 Programming Language Design & Implementation George Ferguson MW 2:00PM - 3:15PM
Design and implementation of programming languages, with an emphasis on imperative languages and on implementation tradeoffs. In-depth examination of 'how programming languages work.' Topics include fundamental language concepts (names, values, types, abstraction, control flow); compilation and interpretation (syntactic and semantic analysis, code generation and optimization); major language paradigms (imperative, object-oriented, functional, logic-based, concurrent). Course projects include assignments in several different languages, with an emphasis on compilation issues. Location Hoyt Hall Room 104
CSC 455-1 Software Analysis & Improv Sreepathi Pai MW 10:25AM - 11:40AM
Programming is the automation of information processing. Program analysis and transformation is the automation of programming itself---how much a program can understand and improve other programs. Because of the diversity and complexity of computer hardware, programmers increasingly depend on automation in compilers and other tools to deliver efficient and reliable software. This course combines fundamental principles and (hands-on) practical applications. Specific topics include data flow and dependence theories; static and dynamic program transformation including parallelization; memory and cache management; type checking and program verification; and performance analysis and modeling. The knowledge and practice will help students to become experts in software performance and correctness. Students taking the graduate level will have additional course requirements and a more difficult project. Location Gavett Hall Room 301
CSC 458-1 Parallel & Distributed Systems Andrew Read-McFarland MW 3:25PM - 4:40PM
Principles of parallel and distributed systems, and the associated implementation and performance issues. Topics covered will include programming interfaces to parallel and distributed computing, interprocess communication, synchronization, and consistency models, fault tolerance and reliability, distributed process management, distributed file systems, multiprocessor architectures, parallel program optimization, and parallelizing compilers. Students taking this course at the 400 level will be required to complete additional readings and/or assignments. Location Dewey Room 2110E
CSC 461-1 Database Systems Eustrat Zhupa MW 10:25AM - 11:40AM
This course presents the fundamental concepts of database design and use. It provides a study of data models, data description languages, and query facilities including relational algebra and SQL, data normalization, transactions and their properties, physical data organization and indexing, security issues and object databases. It also looks at the new trends in databases. The knowledge of the above topics will be applied in the design and implementation of a database application using a target database management system as part of a semester-long group project. Note: Course is only open to undergrad CSC and DSCC students during registration week. Restriction will be lifted Monday, 11/20. Location Dewey Room 2162
CSC 463-1 Data Management Systems Fatemeh Nargesian MW 9:00AM - 10:15AM
This course explores the internals of data engines. Topics covered will include the relational model; relational database design principles based on dependencies and normal forms; query execution; transactions; recovery; query optimization; parallel query processing; NoSQL. Location Gavett Hall Room 312
CSC 478-1 Computer Security Foundations John Criswell MW 6:15PM - 7:30PM
This course will teach students the foundations of computer security. Students will learn what security is, the design principles of secure systems, how security is enforced, and how security is compromised. Topics include access controls, information flow, basic applications of cryptography, buffer overflow attacks, and malware. Prerequisites: CSC 252 or CSC 452 or ECE 200. Location Hylan Building Room 101
CSC 480-1 Computer Models & Limitations Monika Polak MW 2:00PM - 3:15PM
This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness. Prerequisites: CSC 173 and MTH 150. YOU MUST REGISTER FOR A RECITATION WHEN REGISTERING FOR THE MAIN COURSE Location Bausch & Lomb Room 106
CSC 480-10 Computer Models & Limitations - REC Monika Polak W 4:50PM - 6:05PM
This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness. Location Hylan Building Room 306
CSC 480-2 Computer Models & Limitations - REC Monika Polak W 4:50PM - 6:05PM
This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness. Location Lattimore Room 210
CSC 480-3 Computer Models & Limitations - REC Monika Polak W 6:15PM - 7:30PM
This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness. Location Harkness Room 210
CSC 480-4 Computer Models & Limitations - REC Monika Polak R 4:50PM - 6:05PM
This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness. Location Hylan Building Room 105
CSC 480-5 Computer Models & Limitations - REC Monika Polak R 6:15PM - 7:30PM
This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness. Location Meliora Room 218
CSC 480-7 Computer Models & Limitations - REC Monika Polak W 6:15PM - 7:30PM
This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness. Location Meliora Room 218
CSC 480-8 Computer Models & Limitations - REC Monika Polak R 7:40PM - 8:55PM
This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness. Location Bausch & Lomb Room 315
CSC 480-9 Computer Models & Limitations - REC Monika Polak R 3:25PM - 4:40PM
This course studies fundamental computer models and their computational limitations. Finite-state machines and pumping lemmas, the context-free languages, Turing machines, decidable and Turing-recognizable languages, undecidability, NP-completeness. Location Wegmans Room 1005
CSC 482-1 Design & Analysis Efficient Algorithms Eustrat Zhupa TR 9:40AM - 10:55AM
How does one design programs and ascertain their efficiency? Divide-and-conquer techniques, string processing, graph algorithms, mathematical algorithms. Advanced data structures such as balanced tree schemes. Introduction to NP-completeness and intractable combinatorial search, optimization, and decision problems. Prerequisites: (CSC 172 and MTH 150) or MTH172. Students MUST register for a recitation when registering for this course. Location Gavett Hall Room 206
CSC 482-2 Design & Analysis - Rec Eustrat Zhupa T 6:15PM - 7:30PM
How does one design programs and ascertain their efficiency? Divide-and-conquer techniques, string processing, graph algorithms, mathematical algorithms. Advanced data structures such as balanced tree schemes. Introduction to NP-completeness and intractable combinatorial search, optimization, and decision problems. Location Gavett Hall Room 301
CSC 482-3 Design & Analysis - Rec Eustrat Zhupa W 6:15PM - 7:30PM
How does one design programs and ascertain their efficiency? Divide-and-conquer techniques, string processing, graph algorithms, mathematical algorithms. Advanced data structures such as balanced tree schemes. Introduction to NP-completeness and intractable combinatorial search, optimization, and decision problems. Location Gavett Hall Room 301
CSC 482-4 Design & Analysis - Rec Eustrat Zhupa M 6:15PM - 7:30PM
How does one design programs and ascertain their efficiency? Divide-and-conquer techniques, string processing, graph algorithms, mathematical algorithms. Advanced data structures such as balanced tree schemes. Introduction to NP-completeness and intractable combinatorial search, optimization, and decision problems. Location Hylan Building Room 203
CSC 482-5 Design & Analysis - Rec Eustrat Zhupa W 7:40PM - 8:55PM
How does one design programs and ascertain their efficiency? Divide-and-conquer techniques, string processing, graph algorithms, mathematical algorithms. Advanced data structures such as balanced tree schemes. Introduction to NP-completeness and intractable combinatorial search, optimization, and decision problems. Location Hylan Building Room 203
CSC 483-1 Topics in Cryptography Monika Polak MW 9:00AM - 10:15AM
In this course students will learn about the current state of Public Key Cryptography. In particular the NIST (National Institute of Standards and Technology) process to solicit, evaluate, and standardize one or more quantum-resistant public-key cryptographic algorithms will be discussed. Quantum-Resistant Cryptography (QRC) refers to cryptographic systems that are secure against both quantum and classical computers. Such systems may be achieved through classical (i.e. non-quantum) means. The security of many commonly used cryptographic protocols (especially public-key cryptosystems) would be compromised if general-purpose large-scale, fault-tolerant quantum computers became a reality. This course covers the consequences of Quantum Computing and why it poses a threat to currently used cryptographic systems, and then discusses potential Post-Quantum cryptosystems designed to be resistant to such attacks. Students enrolled in this course must have a background in cryptography such as that obtained by taking CSC-281/CSC-481 (Introduction to Cryptography) or similar courses, or permission of the instructor. Location Lechase Room 141
CSC 486-1 Computational Complexity Lane Hemaspaandra MW 2:00PM - 3:15PM
The difference between computable and uncomputable problems and between feasible and infeasible problems. Regarding the latter, what properties of a problem make it computationally simple? What properties of a problem may preclude its having efficient algorithms? How computationally hard are problems? Complete sets and low information content; P=NP?; unambiguous computation and one-way functions; reductions relating the complexity of problems; complexity classes and hierarchies. Prerequisites: CSC 280 Location Gavett Hall Room 301
CSC 489-1 Algorithmic Game Theory Anson Kahng MW 4:50PM - 6:05PM
This class will provide an introduction to topics at the intersection of computer science and economics, including game theory, auctions, incentive-compatible mechanism design, matching algorithms, human computation (e.g., crowdsourcing and peer prediction), trust and reputation systems, and social choice (voting) theory. We hope to convey the fact that the relationship between computer science and economics is a two-way street: It is important to consider incentives and strategic action are important when designing computation-intensive systems, and efficient and robust algorithms enable the deployment of impactful economic ideas. Prerequisites: Familiarity with probability theory, single-variable calculus, linear algebra, and basics of theoretical computer science. No background in economic theory is assumed or required. Students should also be prepared to write code in Python. Please email the instructor with any questions. Location Goergen Hall Room 108
CSC 491-1 Independent Study Michael Scott –
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CSC 495-01 Advanced Research CSC James Allen –
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CSC 495-02 Advanced Research CSC John Criswell –
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CSC 495-03 Advanced Research CSC Zhen Bai –
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CSC 495-04 Advanced Research CSC Chen Ding –
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CSC 495-05 Advanced Research CSC Sandhya Dwarkadas –
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CSC 495-06 Advanced Research CSC Daniel Gildea –
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CSC 495-07 Advanced Research CSC Lane Hemaspaandra –
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CSC 495-08 Advanced Research CSC Ehsan Hoque –
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CSC 495-09 Advanced Research CSC Henry Kautz –
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CSC 495-10 Advanced Research CSC Jiebo Luo –
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CSC 495-11 Advanced Research CSC Fatemeh Nargesian –
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CSC 495-12 Advanced Research CSC Christopher Kanan –
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CSC 495-13 Advanced Research CSC Sreepathi Pai –
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CSC 495-14 Advanced Research CSC Lenhart Schubert –
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CSC 495-15 Advanced Research CSC Michael Scott –
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CSC 495-16 Advanced Research CSC Daniel Stefankovic –
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CSC 495-17 Advanced Research CSC Muthuramakrishnan Venkitasubramaniam –
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CSC 495-18 Advanced Research CSC Chenliang Xu –
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CSC 495-19 Advanced Research CSC Yuhao Zhu –
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CSC 495-20 Advanced Research CSC Aaron White –
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CSC 495-21 Advanced Research CSC Thomas Howard –
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CSC 495-22 Advanced Research CSC Zhiyao Duan –
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CSC 495A-1 Masters Research in Absentia – –
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CSC 574-1 Continuous Algorithms for Optimization and Sampling Jiaming Liang TR 11:05AM - 12:20PM
Traditional algorithms in computer science are designed in a discrete manner. Nonetheless, recent years have witnessed great advances from a continuous perspective, particularly in the design of optimization and sampling algorithms. There is a deep connection between optimization and sampling, either through optimization as the limit of sampling, or through sampling as optimization in the space of probability measures. Motivated by this viewpoint, this course aims to develop a systematic way to design and analyze algorithms for both areas from the continuous perspective. More particularly, this course starts from continuous optimization, discusses stochastic optimization in detail, introduces optimal transport as a bridge connecting optimization and sampling, and finally delves into sampling. Students should be familiar with multivariate calculus, linear algebra, basic probability and statistics, and have good MATLAB or Python programming skills. Prior knowledge of optimization and sampling is helpful but not required. Location Meliora Room 209
CSC 577-1 Advanced Topics in Computer Vision Jiebo Luo TR 9:40AM - 10:55AM
This is a seminar course with varying topics in the area of artificial Intelligence. May not be taught every year. This course covers advanced research topics in computer vision with an emphasis on learning structured representations and embeddings. Approaches for learning from unimodal (e.g., images and videos), and multimodal data (e.g., vision and language, vision and audio) will be covered and include topics from structured predications, deep learning and others. The course will be a mix of lecture, student presentation and discussion. Location Hylan Building Room 203
CSC 594-1 Internship Sandhya Dwarkadas –
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CSC 594-10 Internship Michael Scott –
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CSC 594-11 Internship Daniel Gildea –
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CSC 594-3 Internship Jiebo Luo –
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CSC 594-5 Internship Chenliang Xu –
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CSC 594-6 Internship Yuhao Zhu –
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CSC 594-7 Internship Ehsan Hoque –
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CSC 594-8 Internship Chen Ding –
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CSC 595-1 PhD Research in CSC John Criswell –
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CSC 595-10 PhD Research in CSC Jiebo Luo –
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CSC 595-11 PhD Research in CSC Fatemeh Nargesian –
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CSC 595-12 PhD Research in CSC Ji Liu –
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CSC 595-13 PhD Research in CSC Sreepathi Pai –
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CSC 595-14 PhD Research in CSC Lenhart Schubert –
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CSC 595-15 PhD Research in CSC Michael Scott –
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CSC 595-16 PhD Research in CSC Daniel Stefankovic –
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CSC 595-17 PhD Research in CSC Hangfeng He –
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CSC 595-18 PhD Research in CSC Chenliang Xu –
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CSC 595-19 PhD Research in CSC Yuhao Zhu –
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CSC 595-2 PhD Research in CSC Jiaming Liang –
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CSC 595-20 PhD Research in CSC Aaron White –
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CSC 595-21 PhD Research in CSC Gonzalo Mateos Buckstein –
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CSC 595-22 PhD Research in CSC Thomas Howard –
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CSC 595-23 PhD Research in CSC Gregory Heyworth –
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CSC 595-24 PhD Research in CSC Christopher Kanan –
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CSC 595-25 PhD Research in CSC Mujdat Cetin –
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CSC 595-26 PhD Research in CSC Anson Kahng –
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CSC 595-27 PhD Research in CSC Jian Kang –
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CSC 595-28 PhD Research in CSC Kaave Hosseini –
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CSC 595-29 PhD Research in CSC Adam Sefkow –
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CSC 595-3 PhD Research in CSC Zhen Bai –
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CSC 595-4 PhD Research in CSC Chen Ding –
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CSC 595-5 PhD Research in CSC Sandhya Dwarkadas –
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CSC 595-6 PhD Research in CSC Daniel Gildea –
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CSC 595-7 PhD Research in CSC Lane Hemaspaandra –
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CSC 595-8 PhD Research in CSC Ehsan Hoque –
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CSC 595-9 PhD Research in CSC Yukang Yan –
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CSC 595A-1 PhD Research in Absentia Ehsan Hoque –
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CSC 595B-1 PhD Research in Absentia Abroad Jiebo Luo –
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CSC 595B-2 PhD Research in Absentia Abroad – –
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CSC 597-1 Computer Science Colloquium Anson Kahng M 11:50AM - 1:05PM
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CSC 895-1 Cont of Master's Enrollment – –
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CSC 897-1 Masters Dissertation Daniel Gildea –
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CSC 897A-1 Masters Dissrttn in Absentia Daniel Gildea –
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CSC 899-01 Master's Dissertation Daniel Gildea –
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CSC 899A-1 Masters Dissertation in Absentia – –
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CSC 995-1 Cont of Doctoral Enrollment Daniel Gildea –
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CSC 997-1 Doctoral Dissertation Daniel Gildea –
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CSC 997A-1 Doct Dissertatn in Absentia Ehsan Hoque –
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CSC 999-01 Doctoral Dissertation Daniel Gildea –
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CSC 999A-1 Doctoral Dissertation in Absentia Daniel Gildea –
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