Course Websites

Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: 1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated in the same or separate terms if topics vary.

Solving Real-World Problems with Theoretical Tools. Description: This course explores the powerful intersection of theory and practice in algorithmic problem-solving, teaching students to apply advanced computational tools like LP solvers, SAT/SMT solvers, metaheuristics, and other modern theoretical tools to real-world engineering, optimization, and decision-making challenges. We explain the theory behind these tools to build intuition, but the emphasis is on application: modeling, using solvers effectively, and engineering robust, efficient solutions. Students will gain hands-on experience working on problems in logistics, verification, scheduling, auctions, online algorithms, and LLMs. By the end of the course, students will not only understand the basic underlying theoretical principles, but more importantly, be equipped to integrate these powerful tools into complex, real-world systems. Prerequisites: CS374 or equivalent coursework with a solid foundation in algorithms. Mathematic