I am a Master's student at the University of Illinois at Urbana-Champaign (UIUC) advised by Prof. Tong Zhang and Prof. Julia Hockenmaier.
My research focuses on developing generative models that are not only more intelligent but also reliable. Specifc topics I am currently pursuing include continual learning, curriculum learning, and the design of memory structures and agentic frameworks.
Prior to joining UIUC, I received my Bachelors of Science degree in Computer Science at Duke University. I have worked as a quantitative trader at Optiver US LLC and Old Mission Capital, and as a software engineer at VectorShift, Amazon, and Vertex Protocol.
I am also a classically trained pianist (enjoy).
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RAG-RL: Advancing Retrieval-Augmented Generation via RL and Curriculum Learning
Jerry Huang, Siddarth Madala, Risham Sidhu, Cheng Niu, Hao Peng, Julia Hockenmaier, Tong Zhang
Under review. 2025
We introduce RAG-RL, an answer generation model trained to identify and reason over larger sets of retrieved information using reinforcement learning and curriculum learning.
RAG-RL: Advancing Retrieval-Augmented Generation via RL and Curriculum Learning
Jerry Huang, Siddarth Madala, Risham Sidhu, Cheng Niu, Hao Peng, Julia Hockenmaier, Tong Zhang
Under review. 2025
We introduce RAG-RL, an answer generation model trained to identify and reason over larger sets of retrieved information using reinforcement learning and curriculum learning.
Contextual Relevance: Modeling Context-Conditioned Relevance for Improving Document Reranking
Jerry Huang, Siddarth Madala, Cheng Niu, Julia Hockenmaier, Tong Zhang
Under review. 2025
We investigate the context-dependent nature of LLM-based relevance judgements in the document reranking setting.
Contextual Relevance: Modeling Context-Conditioned Relevance for Improving Document Reranking
Jerry Huang, Siddarth Madala, Cheng Niu, Julia Hockenmaier, Tong Zhang
Under review. 2025
We investigate the context-dependent nature of LLM-based relevance judgements in the document reranking setting.
GUIDE: Towards Scalable Advising for Research Ideas
Yaowenqi Liu, BingXu Meng, Rui Pan, Jerry Huang, Tong Zhang
Under review. 2025
We introduce a scalable advising system for research idea evaluation by leveraging a compressed literature database and fine-tuning techniques.
GUIDE: Towards Scalable Advising for Research Ideas
Yaowenqi Liu, BingXu Meng, Rui Pan, Jerry Huang, Tong Zhang
Under review. 2025
We introduce a scalable advising system for research idea evaluation by leveraging a compressed literature database and fine-tuning techniques.
Fingerprint Matching
For my undergraduate thesis, I investigated the feasibility of using software to generate fingerprint lineups (similar eye-witness lineups) in order to quantify the amount of cognitive bias present in the field of forensic science.
Fingerprint Matching
For my undergraduate thesis, I investigated the feasibility of using software to generate fingerprint lineups (similar eye-witness lineups) in order to quantify the amount of cognitive bias present in the field of forensic science.
