Research

Machine learning under uncertainty.

Peer-reviewed work on out-of-distribution error, optimal transport, safe bandits, and robust optimization, with a bias toward systems that know when not to trust themselves. google scholar ->

2023

NeurIPS main

Characterizing Out-of-Distribution Error via Optimal Transport

Yuzhe Lu, Yilong Qin, Runtian Zhai, Andrew Shen, Ketong Chen, Zhenlin Wang, Soheil Kolouri, Simon Stepputtis, Joseph Campbell, Katia Sycara

ICLR workshop

Predicting Out-of-Distribution Error with Confidence Optimal Transport

Yuzhe Lu, Zhenlin Wang, Runtian Zhai, Soheil Kolouri, Joseph Campbell, Katia Sycara

2022

AISTATS main

Best Arm Identification with Safety Constraints

Zhenlin Wang, Andrew Wagenmaker, Kevin Jamieson

2021

NUS Thesis main

An Information-Theoretic Approach for Distributionally Robust Bayesian Optimization

Zhenlin Wang

Active reviewer service across ML, AI, robotics, information retrieval, scientific computing, and journal venues.
2026
AAMAS Conf AISTATS Conf EAAI Conf ICLR Conf TMLR Journal
2025
CIKM Conf CoRL Conf NeurIPS Conf PRICAI Conf SciPy Conf TMLR Journal