Yifang Chen 陈一方

Senior Research Scientist, Microsoft GenAI, Email: chenyifang at microsoft.com Google Scholar Instagram Twitter

About Me

I am currently a Senior Research Scientist in Microsoft GenAI, working on LLM reasoning, coding and agents.

Prior to this, I completed my Ph.D. degree in Computer Science and Engineering at the University of Washington. I am fortunate to be advised by Prof. Kevin Jamieson and Prof. Simon Shaolei Du. My research focuses on algorithmic data-efficient learning from both empirical and theoretical perspectives.

Prior to starting my Ph.D., I completed my master's and undergraduate degrees in Electrical Engineering at the University of Southern California, advised by Prof. Haipeng Luo. I want to especially thank him and my colleague Chen-Yu Wei, who introduced me to the world of learning theory. During that time, I designed practical and adaptive machine learning algorithms with strong theoretical guarantees, focusing on corrupted and non-stationary online decision-making settings.

Research Interests

• Active learning, data selection, experimental design in LLM

• Representation learning

• Online learning, bandits, Reinforcement learning theory

Selected Publications

1. [NeurIPS24] CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning. (Spotlight)
   Yiping Wang*, Yifang Chen*, Wendan Yan, Alex Fang, Wenjin Zhou, Simon Du, Kevin Jamieson.

2. [ACLFindings24] Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models.
   Gantavya Bhatt*, Yifang Chen*, Arnav M. Das*, Jifan Zhang*, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeffrey Bilmes, Simon S. Du, Kevin Jamieson, Jordan T. Ash, Robert D. Nowak

3. [Journal of DMLR] LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning. [Github]
   Jifan Zhang*, Yifang Chen*, Gregory Canal, Stephen Mussmann, Yinglun Zhu, Simon Shaolei Du, Kevin Jamieson, Robert D Nowak

4. [ICML22] Active Multi-Task Representation Learning.
   Yifang Chen, Simon Du, Kevin Jamieson.

5. [ICML22] First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach. (Long presentation)
   Andrew Wagenmaker, Yifang Chen, Max Simchowitz, Simon S. Du, Kevin Jamieson

6. [ICML’21] Improved corruption robust algorithms for episodic reinforcement learning.
   Yifang Chen, Simon Du, Kevin Jamieson.

7. [COLT’19] A new algorithm for non-stationary contextual bandits: Efficient, optimal and parameter-free.
   Yifang Chen, Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei