Aleksandar Nikolov

Aleksandar Nikolov is an Associate Professor in the Department of Computer Science at the University of Toronto, holding the Canada Research Chair in Algorithms and Private Data Analysis. He is affiliated with the Vector Institute and a faculty fellow at the Schwartz Reisman Institute. His research focuses on theoretical computer science, algorithm design, and their connections to high-dimensional geometry, differential privacy, discrepancy theory, and approximation algorithms. Nikolov completed his PhD at Rutgers University under Muthu's advisement and was a postdoctoral researcher at Microsoft Research.

Research Interests: Nikolov explores high-dimensional geometry's applications in algorithm design, particularly in private data analysis (differential privacy), discrepancy theory, and experimental design. His work bridges geometric tools with computational challenges, including nearest neighbor search and geometric optimization. He also delves into approximation algorithms and sublinear/parallel algorithms for large-scale data analysis.

Awards: Nikolov received the Best Paper Award at SoCG 2015 and a $100 prize from Joel Spencer for resolving Beck's 3-permutations conjecture. His contributions span theoretical computer science with a focus on algorithmic foundations and privacy.

Supervision and Education: He has mentored several graduate and undergraduate students, including current PhD candidates Haohua Tang and Lily Li. Teaching includes advanced courses like CSC2420 (Algorithm Design) and a discrepancy theory course. His research spans over 50 publications, with recent work emphasizing differential privacy and geometric algorithms.

Affiliations: Beyond his academic role, Nikolov collaborates with industry and academic institutions, contributing to Canada's AI ecosystem through Vector Institute and interdisciplinary efforts at Schwartz Reisman.