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An expert in theoretical computer science, he is known for his research on approximation algorithms, online algorithms, distributed algorithms, and the theory of networking.
His work ranges from the purely theoretical to applications of theory, with a focus on computer networking and distributed systems as well as applications in AI and ML. Much of his theoretical work has centered on approximation algorithms, particularly problems involving distances, such as graph spanners and related objects. He has also worked extensively on other types of network design problems, as well as distributed algorithms and processes. His more practical work has included datacenter topology design, resilient routing in overlay networks, fast optimization algorithms using machine-learned advice, and other optimization problems motivated by practice.
His work ranges from the purely theoretical to applications of theory, with a focus on computer networking and distributed systems as well as applications in AI and ML. Much of his theoretical work has centered on approximation algorithms, particularly problems involving distances, such as graph spanners and related objects. He has also worked extensively on other types of network design problems, as well as distributed algorithms and processes. His more practical work has included datacenter topology design, resilient routing in overlay networks, fast optimization algorithms using machine-learned advice, and other optimization problems motivated by practice.
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arxiv(2023)
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arXiv (Cornell University) (2023): 4247-4263
APPROXIMATION AND ONLINE ALGORITHMS, WAOA 2023 (2023): 190-204
INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 151 (2022): 6321-6333
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