Princewill Okoroafor

CS PhD Student | Theory Group | Cornell University

I am a Ph.D. student in the Computer Science department at Cornell University, where I have the great fortune to be advised by Prof. Robert D. Kleinberg. I completed my undergraduate at Harvey Mudd College where I met Prof. Ran Libeskind-Hadas who got me really excited about algorithms and theoretical computer science.

My research interests are broadly in the theoretical aspects of machine learning and computer science, especially in learning theory and reinforcement learning. Currently, I’m working on uncertainty estimation techniques in adversarial online learning.

Besides academic research, I have completed software engineering internships at Microsoft and currently volunteer with Young Data Scientists and MathAction. In my freetime, I enjoy playing soccer and chess.


Oct 1, 2023 I will be speaking at INFORMS 2023 in the session titled “SB07. Frontiers of Algorithmic RM” (Time: Sun Oct 15, 10:45am-12:00pm MST (local time in Phoenix); Location: CC-North 122A)
Nov 1, 2022 My paper with Vaishnavi Gupta, Bobby Kleinberg and Eleanor Goh was accepted to SODA’23.
Aug 30, 2022 Spent summer of 2022 at Toyota Technological Institute, Chicago working with Avrim Blum, Kevin Stangl and Aadirupa Saha on Algorithmic Fairness.

selected publications

  1. Preprint
    Improved Bounds for Calibration via Stronger Sign Preservation Games
    Dagan, Yuval, Daskalakis, Constantinos, Fishelson, Maxwell, Golowich, Noah, Kleinberg, Robert, and Okoroafor, Princewill
    Preprint, 2024
  2. COLT 2024
    Omniprediction for Regression and the Approximate Rank of Convex Functions
    Gopalan, Parikshit,  Okoroafor, Princewill, Raghavendra, Prasad, Shetty, Abhishek, and Singhal, Mihir
    COLT 2024 2024
  3. AISTATS 2024
    On the Vulnerability of Fairness Constrained Learning to Malicious Noise
    Blum, Avrim,  Okoroafor, Princewill, Saha, Aadirupa, and Stangl, Kevin
    Neurips Workshop on Algorithmic Fairness, International Conference on Artificial Intelligence and Statistics (AISTATS 2024) 2023
  4. AISTATS 2024
    Faster Recalibration of an Online Predictor via Approachability
    Okoroafor, Princewill, Sun, Wen, and Kleinberg, Robert
    International Conference on Artificial Intelligence and Statistics (AISTATS 2024) 2024
  5. SODA 2023
    Non-Stochastic CDF Estimation Using Threshold Queries
    Okoroafor, Princewill, Gupta, Vaishnavi, Kleinberg, Robert, and Goh, Eleanor
    Symposium on Discrete Algorithms, 2023