Hi! Welcome to my website. I started as a PhD student in the Industrial Engineering and Operations Research department of Columbia University. I work with the fabulous Shipra Agrawal. I am excited by research questions under the broad umbrella of reinforcement learning and strategic behavior.

In 2021, I graduated from the University of Illinois Urbana-Champaign with a Master in Computer Science, where I was part of Nan Jiang’s RL theory group.

Papers

Optimistic Q-learning for average reward and episodic reinforcement learning Priyank Agrawal, and Shipra Agrawal under review

A Tractable Online Learning Algorithm for the Multinomial Logit Contextual Bandit Priyank Agrawal, Theja Tulabandhula and Vashist Avadhanula to appear in EJOR

Learning-Augmented Mechanism Design: Leveraging Predictions for Facility Location
Priyank Agrawal, Eric Balkanski, Vasilis Gkatzelis, Tingting Ou, and Xizhi Tan
ACM EC 2022

Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration Priyank Agrawal, Jinglin Chen and Nan Jiang
AAAI 2021

Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect Priyank Agrawal and Theja Tulabandhula
UAI 2020

Incentivising Exploration and Recommendations for Contextual Bandits with Payments Priyank Agrawal and Theja Tulabandhula
EUMAS 2020