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.

Research Interests

My research focuses on LLM post-training, agentic coding, and agentic search, with their 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.

Selected Papers

*: equal contribution

For full publication list, please check my Google Scholar profile.

Tech Report 2026

Agentic Coding

Apodex 1.1: Scaling Agentic Intelligence for Complex Work

Technical Report, 2026

Apodex Team

Jiacheng Lin’s Contributions: Agentic Coding

[Paper][Website][Code][Models]

ICLR 2026

LLM Post-Training

SFT Doesn’t Always Hurt General Capabilities: Revisiting Domain-Specific Fine-Tuning in LLMs

International Conference on Learning Representations (ICLR), 2026

Jiacheng Lin, Zhongruo Wang, Kun Qian, Tian Wang, Arvind Srinivasan, Hansi Zeng, Ruocheng Jiao, Xie Zhou, Jiri Gesi, Dakuo Wang, Yufan Guo, Kai Zhong, Weiqi Zhang, Sujay Sanghavi, Changyou Chen, Hyokun Yun, Lihong Li

[Paper]

npj Digit. Med. 2026

LLM Post-Training

Benchmarking and Developing Large Language Models Using One Million Clinical Trials

npj Digital Medicine, 2026

Zifeng Wang*, Jiacheng Lin*, Qiao Jin*, Junyi Gao, Jathurshan Pradeepkumar, Pengcheng Jiang, Zhiyong Lu, Jimeng Sun

[Paper][Project][Dataset][Models]

News Coverage: Nature Biotechnology, MIT Technology Review, HyperAI

TMLR 2025

LLM Post-Training

Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement Learning

Transactions on Machine Learning Research (TMLR), 2025

Jiacheng Lin, Tian Wang, Kun Qian

[Paper][Code]

COLM 2025

Agentic Search

DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning

Conference on Language Modeling (COLM), 2025

Pengcheng Jiang*, Jiacheng Lin*, Lang Cao, Runchu Tian, SeongKu Kang, Zifeng Wang, Jimeng Sun, Jiawei Han

[Paper][Code]

Cell Genomics 2025

Pisces: A multi-modal data augmentation approach for drug combination synergy prediction

Cell Genomics, 2025

Hanwen Xu*, Jiacheng Lin*, Addie Woicik, Zixuan Liu, Jianzhu Ma, Sheng Zhang, Hoifung Poon, Liewei Wang, Sheng Wang

[Paper][Code]

Work Experience

AI Research Intern · Apodex

Apr 2026 – PresentNow

Working with Dr. Beibin Li, Simon Du, and Sheng Wang

Project: Agentic coding.

Machine Learning Research Intern · Keiji AI

Aug – Dec 2025

Advised by Zifeng Wang and Jimeng Sun

Project: Developed a Data Science Assistant/Cursor for clinical data analysis and visualization.

Applied Scientist Intern · Amazon SFAI

May – Aug 2025

Advised by Arvind Srinivasan, Kun Qian, Tian Wang, Hyokun Yun, and Lihong Li

Project: Continual SFT; Bridging SFT and RL; Shopping and Recommendation Agents.

Applied Scientist Intern · Amazon Search

May – Aug 2024

Advised by Kun Qian, Sheng Wang, and Danai Koutra

Project: LLMs for Knowledge Graph Augmented Text Embedding.

Research Intern · Microsoft Research AI4Science

Nov 2022 – Jul 2023

Advised by Lijun Wu and Tao Qin

Project: Multi-modal Scientific Pre-Training Models.

Research Intern · Microsoft Research Asia

Mar – Jun 2022

Advised by Lijun Wu and Tao Qin

Project: Drug Discovery.

Talks