I am a Computer Science Ph.D. candidate at University of Illinois Urbana-Champaign advised by Prof. Jimeng Sun. Before that, I earned my B.Eng and MS degree in Automation at Tsinghua University. I am also working closely with Prof. Sheng Wang and Dr. Lijun Wu.

My research focuses on foundation models (e.g., large language models (LLMs), multi-modal models) and reinforcement learning (RL), with applications in healthcare, biomedicine, and recommendation systems. I am particularly interested in how these models can be used for reasoning, retrieval, and decision-making in complex, real-world scenarios.

• LLM-centric Research: Retrieval (DeepRetrieval, GT2Vec), RAG (math), Knowledge Graphs (GenRES), LLM Efficiency (Cascade Speculative Drafting)
• LLMs/RL + Healthcare: Clinical Trial Foundation Model (Panacea)
• BioMedical Foundation Models: Molecule Foundation Model (Pisces, R²-DDI), Single-cell Foundation Model (EpiAgent)
• LLMs/RL + Recommendation: Bridge RecSys with LLMs using RL (Rec-R1)

I am currently seeking research-oriented internship opportunities for the summer of 2026. Please contact me if you have any recruitment openings.

News

09/2024 Our Cascade Speculative Drafting for Even Faster LLM Inference is accepted by NeurIPS 2024.

05/2024 Starting Applied Scientist Internship at Amazon, Palo Alto.

03/2024 Our GENRES: Rethinking Evaluation for Generative Relation Extraction in the Era of Large Language Models is accepted by NAACL 2024.

01/2024 Our CAMBranch: Contrastive Learning with Augmented MILPs for Branching is accepted by ICLR 2024.

Selected Papers

• Jiacheng Lin, Tian Wang, Kun Qian, Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement Learning, preprint, 2025. [PDF][CODE]
• Pengcheng Jiang*, Jiacheng Lin∗, Lang Cao, Runchu Tian, SeongKu Kang, Zifeng Wang, Jimeng Sun, Jiawei Han, DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning, preprint, 2025. [PDF][CODE]
• Hanwen Xu*, Jiacheng Lin∗, Addie Woicik, Zixuan Liu, Jianzhu Ma, Sheng Zhang, Hoifung Poon, Liewei Wang, Sheng Wang, Pisces: A multi-modal data augmentation approach for drug combination synergy prediction, Cell Genomics, 2025. [PDF][CODE]
• Jiacheng Lin∗, Hanwen Xu∗, Addie Woicik, Jianzhu Ma and Sheng Wang, Pisces: A cross-modal contrastive learning approach to synergistic drug combination prediction, RECOMB, 2023. [PDF][CODE]
• Jiacheng Lin, Lijun Wu, Jinhua Zhu, Xiaobo Liang, Yingce Xia, Shufang Xie, Tao Qin and Tie-Yan Liu, R²-DDI: Relation-aware Feature Refinement for Drug-Drug Interaction Prediction, Briefings in Bioinformatics, Volume 24, Issue 1, 2023. [PDF][CODE]