About me
I am currently a scientist at AWS AI Fundamental Research. I try to understand language models' mechanisms, behaviors and how to better utilize them.
My recent research focus has been on Agentic Reinforcement Learning, such as tool-integrated reasoning and credit assignment in long-horizon RL. Check out my recent works about
credit assignment in GRPO, RL for machine learning agents and improving reasoning faithfulness of RAG agent. Full list of publications can be found @Google Scholar.
I completed my Ph.D. study from Utah NLP, advised by Prof. Vivek Srikumar and Prof. Bei Wang.
I am open to collaborations, feel free to reach out to me at zhichaoxu14@gmail.com.
@Twitter @BlueSky @Google Scholar
Recent News
- 11/2023: Vertical Allocation-based Fair Exposure Amortizing in Ranking receives Honorable Mention @SIGIR-AP2023.
- 07/2023: Automated Generation of Security-Centric Descriptions for Smart Contract Bytecode received Distinguished Paper Award @ISSTA2023.
Education
- PhD in Computer Science
University of Utah, Salt Lake City, UT, 2020 Fall - 2024 Fall
- MS in Computer Science
Rutgers University, the State University of New Jersey, New Brunswick, NJ, 2018 Fall - 2020 Summer
- BS in Applied Statistics
Shanghai University of Finance and Economics, Shanghai, 2014 Fall - 2018 Summer
Internships
- Research Intern,
mentored by Dr. Junpeng Wang
Visa Research, Foster City, CA, 05.2024 - 08.2024
- Student Researcher,
mentored by Dr. Jiepu Jiang
Google Research, Mountain View, CA, 05.2023 - 08.2023
- Research Intern,
mentored by Dr. Daniel Cohen
and Dr. Hemank Lamba
Dataminr, New York City, NY, 09.2022 - 12.2022
- Research Intern, mentored by
Dr. Sebastian Bruch
and Dr. Hemank Lamba
Dataminr, New York City, NY, 05.2022 - 08.2022
- Data Science Intern
SAP Lab, Shanghai, CN, 12.2017 - 05.2018
Academic Services
- Conference Reviewer: ACL, ACL ARR, CCL, TheWebConf, SIGIR, SIGIR-AP, WSDM, RecSys
- Journal Reviewer:
ACM Transactions on Information Systems (TOIS),
IEEE Transactions on Affective Computing (Affective Compute),
IEEE Transactions on Artificial Intelligence (T-AI),
Computational Linguistics (CL)
- Workshop Reviewer: DLP-KDD, DLP-RecSys, inter alia
Teaching
- TA, CS 6350 Machine Learning, 2024 Spring, University of Utah, School of Computing, lectured by Prof. Vivek Srikumar.
- Lead TA, CS 6140 Data Mining, 2023 Spring, University of Utah, School of Computing, lectured by Prof. Ana Marasovic.
- TA, CS 2100 Discrete Structures, 2022 Fall, University of Utah, School of Computing, lectured by Prof. Bei Wang Philips.
- TA, CS 6140 Data Mining, 2022 Spring, University of Utah, School of Computing, lectured by Prof. Qingyao Ai.
