
About
I'm a fourthyear PhD student in Computer Science at Stanford University, affiliated with Stanford AI Lab. I am fortunate to be advised by Tengyu Ma. My current research interests broadly lie in machine learning, particularly deep learning theory, representation learning, and optimization.
In the past, I have had the opportunity to work with Suvrit Sra on convex optimization, and with Roger Grosse on optimization for neural networks.
Before Stanford, I was an undergraduate at Yao Class led by Professor Andrew ChiChih Yao at Tsinghua University.

Publish under name Jeff Z. HaoChen

Beyond NTK with Vanilla Gradient Descent: A MeanField Analysis of Neural Networks with Polynomial Width, Samples, and Time
Arvind Mahankali, Jeff Z. HaoChen, Kefan Dong, Margalit Glasgow, Tengyu Ma
NeurIPS, 2023 [PDF]

Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models
Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung
ACL, 2023 [PDF]

A Theoretical Study of Inductive Biases in Contrastive Learning
Jeff Z. HaoChen, Tengyu Ma
ICLR, 2023 [PDF]

Diagnosing and Rectifying Vision Models using Language
Yuhui Zhang, Jeff Z. HaoChen, ShihCheng Huang, KuanChieh Wang, James Zou, Serena Yeung
ICLR, 2023 [PDF]

Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations
Jeff Z. HaoChen, Colin Wei, Ananya Kumar, Tengyu Ma
NeurIPS, 2022 [PDF]

Amortized Proximal Optimization
Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger Grosse
NeurIPS, 2022 [PDF]

Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation
Kendrick Shen, Robbie Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang
ICML, 2022 [PDF]

Selfsupervised Learning is More Robust to Dataset Imbalance
Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma
ICLR, 2022 (spotlight) [PDF]

Provable Guarantees for SelfSupervised Deep Learning with Spectral Contrastive Loss
Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma
NeurIPS, 2021 (oral) [PDF]

Shape Matters: Understanding the Implicit Bias of the Noise Covariance
Jeff Z. HaoChen, Colin Wei, Jason D. Lee, Tengyu Ma
COLT, 2021 [PDF]

Metalearning Transferable Representations with a Single Target Domain
Hong Liu, Jeff Z. HaoChen, Colin Wei, Tengyu Ma
Preprint, 2020 [PDF]

Random Shuffling Beats SGD after Finite Epochs
Jeff Z. HaoChen, Suvrit Sra
ICML, 2019 [PDF]

