معرفی
Hao Peng is an Assistant Professor at the Siebel School of Computing and Data Science, part of the Grainger College of Engineering at the University of Illinois Urbana-Champaign. He holds a B.S. from Peking University (2016) and a Ph.D. from the University of Washington’s Paul G. Allen School of Computer Science & Engineering (2022). His research focuses on Natural Language Processing (NLP), Machine Learning, Large Language Models (LLMs), and AI for Science, with particular emphasis on improving LLM efficiency, factuality, and interdisciplinary applications. Recent courses include 'CS 598 PEN - Efficiency in NLP' and 'CS 598 PEN - LLM Post-pretraining.'
Hao’s work spans advancing LLM generalization capabilities, mitigating hallucinations, and addressing hardware constraints. In 2024, he co-authored an award-winning paper on 'LM-Infinite,' enabling zero-shot extreme length generalization in LLMs. He collaborates internationally, including with the Hebrew University of Jerusalem under a joint research grant since 2019. He also contributes to Argonne National Laboratory’s AI initiatives through invited lectures.
- Education:
- B.S., School of Electronics Engineering and Computer Science, Peking University, 2016
- Ph.D., Paul G. Allen School of Computer Science & Engineering, University of Washington, 2022
- Key Collaborations:
- Interdisciplinary research with Hebrew University of Jerusalem (2025)
- Joint seed grant program with HUJI since 2019
His advising includes graduate student Chi Han, who contributed to the NAACL award-winning work. Grants and seed funding focus on accelerating economic development through tech innovation. No specific lab affiliations are explicitly mentioned, but his research aligns with Argonne’s AI Distinguished Lecture series and open-source platforms like OpenDevin/OpenHands.
