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Course Criteria
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1.00 Credits
Describes the convergence of computer graphics and computer vision with photography. Its goal is to overcome the limitations of traditional photography using computational techniques to enhance the way we capture, manipulate, and interact with visual media. Topics covered: cameras, human visual perception, image processing and manipulation, image based lighting and rendering, high dynamic range, single view reconstruction, photo quality assessment, non photorealistic rendering, the use of Internet-scale data, and more. Students are encouraged to capture and process their own data. Prerequisites: previous programming experience, basic linear algebra, calculus, and probability; previous knowledge of computer graphics or computer vision.
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1.00 Credits
We will study various algorithmic problems that arise in the study of topological phenomena, such as winding number, turning number, knot polynomials, topology of covering spaces (especially Riemann surfaces), and discrete Morse theory. The mathematical topics will be briefly introduced before we move to computations, but some a priori mathematical sophistication will make the course more valuable to the student. Prerequisite: CSCI 0160, 0180, or 0190.
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1.00 Credits
Geometric algorithms in two and three dimensions. Algorithmic and geometric fundamentals. Point location, convex hulls, proximity (Voronoi diagrams, Delaunay triangulations), intersections, the geometry of rectangles. Prerequisites: CSCI 0160, 0170, or 0190; and CSCI 0220.
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1.00 Credits
A project-centered course focused on technological, paradigm, and design innovations for game development. As teams, students will propose and implement a project demonstrating a novel technology for gaming. Examines the current state and future of game development through a seminar of speakers active in game development and research. A strong computer science or engineering background is recommended.
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1.00 Credits
The course is devoted to computational and statistical methods as well as software tools for DNA, RNA, and protein sequence analysis. The focus is on understanding the algorithmic and mathematical foundations of the methods, the design of associated genomics software tools, as well as on their applications. Topics include: sequence alignment, genome assembly, gene prediction, regulatory genomics, and SNP's variation. The course is open to computer and mathematcial sciences students as well as biological and medical students.
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1.00 Credits
We review recent as well as well-established advanced techniques in combinatorial optimization and constraint satisfaction. Students will study and individually present research papers and work on challenging software projects in small teams. Prerequisites: CSCI 0160, 0180, or 0190; and CSCI 0510; and CSCI 1490 or 2580, or instructor permission.
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1.00 Credits
This course will introduce algorithms from machine learning and combinatorial optimization with a focus on their application to biological data. Topics will include problems in phylogenetic inference, population genetics, and biological interaction networks.
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1.00 Credits
Independent study in various branches of Computer Science. Section numbers vary by instructor. Please check Banner for the correct section number and CRN to use when registering for this course.
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1.00 Credits
Important current topics in computer graphics. Course includes reading and discussing current research papers, multiple assignments and preliminary projects in which students implement recent papers, and a demanding final integrative project done in small groups. Prerequisite: CSCI 0320 or CSCI 0360, and CSCI 1230.
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1.00 Credits
In-depth treatment of advanced issues in database management systems. Topics vary from year to year and may include distributed databases, mobile data management, data stream processing and web-based data management. Prerequisite: CSCI 1270.
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