Thodoris Lykouris


Thodoris Lykouris

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Thodoris Lykouris is an Assistant Professor of Operations Management at the MIT Sloan School of Management. 

His research focuses on data-driven sequential decision-making and spans across the areas of machine learning, dynamic optimization, and economics. Prior to his current position, he was a postdoctoral researcher at Microsoft Research NYC where he was part of the machine learning group. 

His dissertation was selected as a finalist in the Dantzig dissertation award competition. His papers have also been selected as finalists in the INFORMS Nicholson and Applied Probability Society best student paper competitions. He is also the recipient of a Google Ph.D. Fellowship and a Cornell University Fellowship.

Thodoris holds a Diploma in electrical and computer engineering from National Technical University of Athens (Greece) and a PhD in computer science from Cornell University, where he was advised by Éva Tardos.



"Advancing Subgroup Fairness via Sleeping Experts."

Avrim Blum and Thodoris Lykouris. In Proceedings of the 11th Innovations in Theoretical Computer Science Conference (ITCS 2020), Seattle, WA: January 2020.

"Bandits with Adversarial Scaling."

Thodoris Lykouris, Vahab Mirrokni, and Renato Paes Leme. In Proceedings of the 37th International Conference on Machine Learning (ICML 2020), San Diego, CA: July 2020.

"Bayesian Decision-making Under Misspecified Priors with Applications to Meta-learning."

Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu, Thodoris Lykouris, Miroslav Dudík, and Robert Schapire. In Proceedings of the 35th Conference on Neural Information Processing Systems, NeurIPS 2021, December 2021.

"Competitive Caching with Machine Learned Advice."

Lykouris, Thodoris and Sergei Vassilvitskii. Journal of the ACM Vol. 68, No. 4 (2021): 1-25. Video.

"Competitive Caching with Machine Learned Advice."

Thodoris Lykouris and Sergei Vassilvitskii. In Proceedings of the 35th International Conference on Machine Learning (ICML 2018), Stockholm, Sweden: July 2018.

"Constrained Episodic Reinforcement Learning in Concave-convex and Knapsack Settings."

Kianté Brantley, Miroslav Dudik, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, and Wen Sun. In Proceedings of the 34th Annual Conference on Neural Information Processing Systems (NeurIPS 2020), San Diego, CA: December 2020.

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