About me
I am currently a scientist at AWS Bedrock AI. I study language models' mechanisms, behaviors and how to better utilize them.
I completed my Ph.D. study from Kahlert School of Computing, University of Utah, advised by Prof. Vivek Srikumar and Prof. Bei Wang . I was affliated with Utah NLP and SCI Institute.
During my Ph.D., I worked on deep learning methods for NLP and Information Retrieval, involving retrieval-augmentioned generation, in-context learning, decoding methods for natural language generation, dense retrieval, recommendation and learning-to-rank.
I am open to collaborations, feel free to reach out to me at zhichaoxu14@gmail.com. Let's cook something cool together!
@Twitter @BlueSky @Google Scholar
Recent News
- 03/2025: State Space Models are Strong Text Rerankers [preprint] accepted to NAACL 2025 RepL4NLP Workshop.
- 02/2025: Two new manuscripts on arXiv: A Survey of Model Architectures for Information Retrieval [preprint] and A Systematic Survey of Automatic Prompt Optimization Techniques [preprint].
- 12/2024: Two new manuscripts on arXiv: Multi-agent Retrieval-augmented Generation [preprint] and State Space Models for Reranking [preprint].
- 09/2024: Two papers accepted to Findings of EMNLP, evaluating safety dimensions of LLM compression [preprint] and empathetic dialogue utterances [preprint].
- 06/2024: Counterfactual Editing for Search Result Explanation accepted to ICTIR 2024, check [preprint].
- 03/2024: In-Context Example Ordering Guided by Label Distributions accepted to Findings of NAACL 2024, check [preprint].
- 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, DLP-KDD, TheWebConf, SIGIR, RecSys
- Workshop Reviewer: DLP-KDD, DLP-RecSys
- Journal Reviewer: TOIS
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.
