Yang (Justin) Meng

About

I am a second-year PhD student in Computer Science at the University of Chicago, where I previously received my Bachelor's degree in Mathematics and Computer Science. I am advised by Prof. Yuxin Chen.

My research focuses on continual learning for foundation models, agents, and physical AI. I study how learning systems can acquire, transfer, and refine knowledge through ongoing interaction and accumulated experience. Another thread of my research explores machine learning for scientific discovery, with projects spanning autonomous labs, PDE modeling, quantum material growth, and spectrometer design.

I am actively looking for Summer 2027 internship opportunities. Feel free to reach out if you are interested in discussing related research or potential collaborations!

Publications & Preprints

Shared Actors Need Not Share Critics: Effects of Value Mismatch in Parallel Reinforcement Learning
Zhenya Liu, Yang Meng, Zhuokai Zhao, Xuefeng Liu^†, Yuxin Chen^†
NeurIPS 2026 Dynafront[paper]
Rethinking Transfer in Continual Learning: A Replay-Based Realisation
Yang Meng, Zhenya Liu, Zhuokai Zhao^†, Yuxin Chen^†
NeurIPS 2026 CL4FMAgents[paper]
Active Feature Acquisition by Distilling an Oracle Teacher
Yang Meng, Zixin Ding, Robert L. Grossman, Yuxin Chen
Under review
World Model as High-Fidelity Simulators of Scientific Processes
Yang Meng, Sherry Yang
Under review
Accelerating PDE Surrogates via RL-Guided Mesh Optimization
Yang Meng, Ruoxi Jiang, Zhuokai Zhao, Chong Liu, Rebecca Willett, Yuxin Chen
AISTATS 2026[paper]
Personalized Incentive Alignment: Correcting Utility-Driven Selection Bias in A/B Tests
Jiachun Li, Yang Meng, David Simchi-Levi, Chonghuan Wang
AISTATS 2026
CRF-based Recognition of Invasive Fungal Infection Concepts in CHIFIR Clinical Reports
Yang Meng, Vlada Rozova, Karin Verspoor
ALTA 2023

Yang (Justin) Meng

About

Publications & Preprints

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