Greetings! I am an Assistant Professor at Stevens Institute of Technology. I am also affiliated with Stevens Institute for Artificial Intelligence (SIAI) and the Center for Research Toward Advancing Financial Technologies (CRAFT).
I’m looking for highly motivated, hard-working Ph.D. students as well as RAs to work with me in data science and interdisciplinary trustworthy GenAI. Feel free to shoot me an email with your CV. Once we have a commitment to each other, I will exert my utmost effort to help you!
I received my Ph.D. from Rutgers University in 2023 where I was fortunate to work with Dr. Hui Xiong.
My work has been published in top venues of machine learning, artificial intelligence and information systems, including refereed journals (IEEE TKDE, IEEE BigData) and conference proceedings (NeruIPS, KDD, EMNLP, AAAI, IJCAI, SIGIR, ICDM, CIKM, CIST, etc.). Some of my working papers are under review at UTD and FT50 journals.
Research Interests
1. Understanding LLM Mechanistics for Trustworthiness
- Copyright Compliance: Detect and prevent intellectual property violations in LLM outputs.
- Safety Prediction: Forecasting and early intervetion for risky behaviors at inference time.
- Theory of Mind (ToM): Study LLMs’ ability to simulate reasoning and align with human values.
2. Enhancing Fundamental Reasoning via Reinforcement Learning
- Process-Based Reward Models: Promote logical reasoning via verifiable rewards and reinforcement learning.
- Structural Attention: Improve handling of hierarchical and context-rich inputs.
- Moral & Legal Reasoning: Enable alignment with social norms and legal standards.
3. Broadening Applications & Domain Adaptation
- LLM Agents in Finance: Support investment, compliance, and risk tasks.
- Multi-Modal Document Understanding: Integrate text, tables, and charts for regulatory documents.
- Robust Domain Adaptation: Strengthen LLMs for high-stakes, domain-specific use cases.
News
05/2025: Check our NAACL LLM copyright tutorial slides here.
05/2025: Our position paper on handling complex copyright risks accepted by ICML-2025.
05/2025: Two papers on alignment and reasoning agent accepted by ACL-2025.
01/2025: A paper on data valuation accepted by NAACL-2025!
12/2024: Copyright tutorial accepted by NAACL-2025, see you at Albuquerque!
11/2024: We are glad to receive the award from NSF NAIRR Pilot Program.
11/2024: We’ll be hosting a tutorial at AAAI-2025 on LLM copyright risks, memorization, and ethical alignment!
09/2024: One paper on Financial multi-agent system accepted to NeurIPS (Main).
09/2024: One paper on analyzing copyright behavior of LLMs accepted to EMNLP (Main).
08/2024: Will present LLM copyright study at CIKM Data-centric AI workshop.
07/2024: Awarded the OpenAI Researcher Access Program.
04/2024: One paper on Graph Neural Network got accepted to IJCAI 2024.
03/2024: Collaboration team received a $5,000 grant supporting research on AI labor ecosystem.
01/2024: Invited to serve as a reviewer for MIS Quarterly.
12/2023: Glad to receive the Best Student Paper Award at ICIS 2023!
12/2023: One paper on Hierarchical Multi-Label Classification got accepted to AAAI 2024!
11/2023: One paper on Sequence Learning for Trading got accepted to IEEE TKDE!
09/2023: Invited to serve as a reviewer for INFORMS Journal on Computing.
09/2023: Invited to serve as a reviewer for Nature Communications.
03/2023: Invited to serve as a reviewer for AMCIS 2023.
02/2023: Invited to serve as a PC member for KDD 2023.
09/2022: Glad to receive the Student Scholarship from INFORMS Workshop on Data Science!
09/2022: Invited to serve as a PC member for WITS 2022!
08/2022: Two papers got accepted to INFORMS Workshop on Data Science.
08/2022: One paper got accepted to CIST 2022.
08/2022: One paper on product representation learning got accepted to IEEE TKDE.
08/2022: Invited to serve as a PC member for AAAI 2023.
07/2022: Invited to serve as a session chair for KDD 2022.
05/2022: Thrilled to receive the Dean’s Dissertation Fellowship from Rutgers, thank you Rutgers!
04/2022: Will serve as a session chair at INFORMS 2022.
12/2021: One paper on Knowledge Graph reasoning got accepted to AAAI’22 (15% acceptance rate).
11/2021: Invited to serve as a PC member for KDD’22 Applied Data Science Track.
10/2021: Gave a talk about Domain-oriented BERT at AI Times (by Tsinghua University).
08/2021: Invited to serve as a PC member for AAAI’22, WSDM’22.
07/2021: Invited to serve as a PC member for IJCAI’22.
05/2021: One paper accepted to KDD’21.
04/2021: Passed my dissertation proposal defense, glad to be Ph.D. candidate now!
01/2021: Will join Amazon as a research intern.
12/2020: One paper on Corporate Profiling accepted to AAAI’21.
11/2020: Invited to serve as a PC member for WWW’21.
10/2020: Invited to serve as a PC member for IJCAI’21.
09/2020: Invited to serve as a PC member for AAAI’21.
Professional Services
Journal Reviewer:
- Nature Communications
- IEEE Transactions on Knowledge and Data Engineering (TKDE)
- IEEE Transactions on Image Processing (TIP)
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
- MIS Quarterly
- Pattern Recognition
- INFORMS Journal on Computing
- Information & Management
- Electronic Commerce Research and Applications
Program Committee Member:
- ACM Conference on Knowledge Discovery and Data Mining (SIGKDD), 2022-2024
- Annual Meeting of the Association for Computational Linguistics (ACL), 2022
- Empirical Methods in Natural Language Processing (EMNLP), 2024
- AAAI Conference on Artificial Intelligence (AAAI), 2021-2024
- International Joint Conference on Artificial Intelligence (IJCAI), 2021, 2022
- Workshop on Information Technologies and Systems (WITS), 2022
- International Conference on Information Systems (ICIS), 2022
- Pacific Asia Conference on Information Systems (PACIS), 2022
- International Conference on Information and Knowledge Management (CIKM), 2020
- ACM International Conference on Web Search and Data Mining (WSDM), 2022
Session Chair:
- INFORMS Annual Meeting, 2022
- Session of AI-driven Business Analytics: New Advances and Applications
- The 28th ACM SIGKDD, 2022
- Session of “Graph Learning and Social Networks”
Prospective Students
Stevens Institute of Technology is a premier, private research university situated in Hoboken, New Jersey. Stevens is the best school for engineering, science, and quantitative finance in the NY metro area and one of the best in the US. It is ranked #76 out of 439 National Universities according to US News report. If interested, please apply to our Data Science Ph.D. program and mention my name as expected advisor.
Ph.D. Student Requirements
- With a bachelor’s or master’s degree in Computer Science, Mathematics, Statistics, Finance, or other related disciplines.
- Have a strong passion for academic research, a thirst for knowledge, curiosity, and enjoyment of the investigative process.
- Hardworking and a high sense of responsibility.
- Excellent communication skills and proficiency in English.
Industry Experiences
- Amazon Science, Product Graph Team, Applied Scientist Intern, 2021.05 - 2021.08
- NEC Laboratories America, Data Science Team, Research Intern, 2020.06 - 2020.08
- NEC Laboratories America, Data Science Team, Research Intern, 2019.06 - 2019.08
- Baidu Research, Talent Intelligence Center, Research Intern, 2018.06 - 2018.08
Resources for Students
- Awesome Tips for Ph.D. Students from Dr. Jia-Bin Huang
- How to Do Research?
- Planning Paper Writing
- Shortening Papers to Fit Page Limits
- How to Write Rebuttals
