معرفی
Yury Makarychev is an Associate Professor at the Toyota Technological Institute at Chicago (TTIC) and holds a part-time appointment as an Associate Professor in the Department of Computer Science at the University of Chicago. His research focuses on the theoretical foundations of computer science, particularly in algorithm design, approximation algorithms, and computational geometry. He is a core member of the Theoretical Computer Science Group, bridging connections between computer science and mathematical disciplines like physics and statistics.
Yury's academic journey includes teaching courses such as Geometric Methods in Computer Science and Computational and Metric Geometry. His recent work emphasizes fair clustering algorithms, metric embeddings, and certified algorithms beyond worst-case analysis. Notable contributions include approximation algorithms for correlation clustering, k-means, and graph partitioning problems. He has advised PhD students including Naren Manoj, Max Ovsiankin, and Omshi Samal.
Yury organizes workshops on topics like algorithms for massive datasets and high-dimensional analysis. His research has been recognized through grants such as the NSF Collaborative Medium Research Project. Professional contributions include editorial roles, program committee memberships, and impactful publications in venues like STOC, FOCS, and ICML.
