The finalists and winner of the 2021 Applied Probability Society student paper competition, as announced during the 2021 INFORMS meeting, are (in alphabetical order):
Mark Gluzman (Cornell U.) for the paper ``Queueing Network Controls via Deep Reinforcement Learning'' (faculty co-author: Jim Dai)
Omar Mouchtaki (Columbia U.) for the paper ``How Big Should Your Data Really Be? Data-Driven Newsvendor and the Transient of Learning'' (faculty co-author: Omar Besbes)
Yunbei Xu (Columbia U.) for the paper ``Towards Optimal Problem Dependent Generalization Error Bounds In Statistical Learning Theory'' (faculty co-author: Assaf Zeevi)
Xiangyu Zhang [WINNER] (Cornell U.) for the paper ``Restless Bandits with Many Arms: Beating the Central Limit Theorem'' (faculty co-author: Peter Frazier)
The recordings of their INFORMS presentations remain available on the meeting's website (see session VMC21)
Itai Gurvich, Chair of the competition committee
On behalf of the committee members: Alessandro Arlotto, Sayan Banerjee, Anton Braverman, Amarjit Budhiraja, David Gamarnik, Varun Gupta, Junfei Huang, Rouba Ibrahim, Peter Jacko, Henry Lam, Nan Liu, Yunan Liu, Debankur Mukherjee, Giang Nguyen, Mariana Olvera-Cravioto, Lerzan Örmeci, Erhun Özkan, Jamol Pender, Pengyi Shi, Weina Wang, Linwei Xin, Zeyu Zheng, Yuan Zhong, Enlu Zhou, Xi Chen, Angela Zhou, Jiaming Xu, Bora Keskin, Qiaomin Xie, Thodoris Lykouris, Jonathan Niles-Weed.