About me

• PhD student at Department of Biomedical Informatics and Medical Education, University of Washington
• Research Interests: Longitudinal Electronic Health Record; AI for Health; LLM for EHR; Patient Trajectory
• Other Interests: Skiing, Hiking, Traveling, Photography
• I’m open to research internship opportunities in summer 2026.

Education

• Ph.D. student in Biomedical Informatics, 2023—2027 (expected)
  • University of Washington, United States
  • Advisor: Ruth Etzioni (Professor), Meliha Yetisgen (Professor)
• B.Eng. in Electronic Engineering, 2019—2023
  • Minor: Statistics
  • Tsinghua University, China
  • Advisor: Bowen Zhou (Chair Professor), Sheng Yu (Associate Professor)
• Exchange, 2022
  • KTH Royal Institute of Technology, Sweden

News

• Jul 2025: Our paper “TrajSurv: Learning Continuous Latent Trajectories from Electronic Health Records for Trustworthy Survival Prediction” is accepted by Machine Learning for Healthcare (MLHC) 2025.
• Jun 2025: I join Futurewei as a research intern and will work on agentic memory system during the summer.
• May 2025: We release “MARTI: A Framework for LLM-based Multi-Agent Reinforced Training and Inference” on GitHub.
• Mar 2025: Our abstract “Population-Level Tobacco Cessation Outcomes Associated with Implementing Whole Health at the Veterans Health Administration” is accepted by AcademyHealth Annual Research Meeting as a poster.
• Dec 2024: Our abstract “The Effect of Real-World Diffusion of CIH Therapies and Whole Health Coaching on Tobacco Cessation Outcomes in the Veterans Health Administration” is accepted by ICIMH 2025 as an oral presentation with a travel award.
• Nov 2024: I will work with Prof. Meliha Yetisgen on biomedical LLMs.
• Sep 2024: Our paper “UltraMedical: Building Specialized Generalists in Biomedicine” is accepted by NeurIPS 2024 Datasets & Bencharmarks track as a poster (Spotlight).
• Jul 2024: Our paper “Large Language Models as Biomedical Hypothesis Generators: A Comprehensive Evaluation” is accepeted by COLM 2024.
• May 2024: Our paper “CoRTEx: Contrastive Learning for Representing Terms via Explanations with Applications on Constructing Biomedical Knowledge Graphs” is published on Journal of the American Medical Informatics Association (JAMIA).
• May 2024: I join Fred Hutch Cancer Center as a graduate non-employee and will work with Prof. Ruth Etzioni on the predictive models of prostate cancer using EHR.
• Jan 2024: I join VA Puget Sound as a Without Compensation (WOC) research assistant and will work with Prof. Steve Zeliadt on the analysis of Whole Health in VA.
• Oct 2023: Our paper “Large Language Models are Zero Shot Hypothesis Proposers” is accepted by Instruction Workshop @ NeurIPS 2023 as a poster presentation.
• Sep 2023: I join University of Washington as a Ph.D. student in Biomedical and Health Informatics.
• Jul 2023: Our paper “Hierarchical Pretraining for Biomedical Term Embeddings” is accepted by Conference on Computational Intelligence Methods for Bioinformatics & Biostatistics (CIBB) 2023 as an oral presentation.
• Jun 2023: I graduate from Tsinghua University with a B.Eng. degree in Electronic Engineering and a B.S. minor degree in Statistics.
• May 2022: Our paper “Automatic Biomedical Term Clustering by Learning Fine-grained Term Representations” is accepted by ACL 2022 BioNLP Workshop as a poster presentation.
• Mar 2022: Our paper “BIOS: An Algorithmically Generated Biomedical Knowledge Graph” is available on arXiv.

Awards

• Travel Award (scholarship awarded by ICIMH 2025), 2025
• Top Scholar Award (fellowship awarded by University of Washington), 2023
• Arts Excellence Award (scholarship awarded by Tsinghua University), 2022
• Comprehensive Excellence Award (scholarship awarded by Tsinghua University), 2021
• Comprehensive Excellence Award (scholarship awarded by Tsinghua University), 2020

Publications

(¹ indicates equal or core contribution)

• Kaiyan Zhang¹, Runze Liu¹, Xuekai Zhu¹, Kai Tian¹, Sihang Zeng¹, Guoli Jia¹, Yuchen Fan¹, Xingtai Lv¹, Yuxin Zuo¹, Che Jiang¹, Ziyang Liu, Jianyu Wang, Yuru Wang, Ruotong Zhao, Ermo Hua, Yibo Wang, Shijie Wang, Junqi Gao, Xinwei Long, Youbang Sun, Zhiyuan Ma, Ganqu Cui, Lei Bai, Ning Ding, Biqing Qi, Bowen Zhou, “MARTI: A Framework for Multi-Agent LLM Systems Reinforced Training and Inference”, 2025, GitHub repo. (code)
• Sihang Zeng, Lucas Jing Liu, Jun Wen, Meliha Yetisgen, Ruth Etzioni, Gang Luo, “TrajSurv: Learning Continuous Latent Trajectories from Electronic Health Records for Trustworthy Survival Prediction”, 2025, MLHC
• Sihang Zeng, Scott Coggeshall, Ethan Rosser, Stephanie L. Taylor, Diana Burgess, Gang Luo, Steven Zeliadt, “Population-Level Tobacco Cessation Outcomes Associated with Implementing Whole Health at the Veterans Health Administration”, 2025, AcademyHealth ARM. (paper)
• Sihang Zeng, Scott Coggeshall, Ethan Rosser, Stephanie L. Taylor, Diana Burgess, Gang Luo, Steven Zeliadt, “The Effect of Real-World Diffusion of CIH Therapies and Whole Health Coaching on Tobacco Cessation Outcomes in the Veterans Health Administration”, 2025, ICIMH (oral)
• Kaiyan Zhang, Sihang Zeng, Ermo Hua, Ning Ding, Zhang-Ren Chen, Zhiyuan Ma, Haoxin Li, Ganqu Cui, Biqing Qi, Xuekai Zhu, Xingtai Lv, Hu Jinfang, Zhiyuan Liu, Bowen Zhou, “UltraMedical: Building Specialized Generalists in Biomedicine”, 2024, NeurIPS Datasets & Bencharmarks (spotlight). (paper, code, huggingface)
• Huaiyuan Ying, Zhengyun Zhao, Yang Zhao, Sihang Zeng, Sheng Yu, “CoRTEx: Contrastive Learning for Representing Terms via Explanations with Applications on Constructing Biomedical Knowledge Graphs”, 2024, JAMIA. (paper)
• Bryan Cai¹, Sihang Zeng¹, Yucong Lin, Zheng Yuan, Doudou Zhou, Lu Tian, “Hierarchical Pretraining for Biomedical Term Embeddings”, 2023, Conference on Computational Intelligence Methods for Bioinformatics & Biostatistics (oral). (paper, huggingface)
• Sihang Zeng¹, Zheng Yuan¹, Sheng Yu, “Automatic Biomedical Term Clustering by Learning Fine-grained Term Representations”, 2022, ACL 2022 BioNLP Workshop. (paper, code, huggingface)
• Sheng Yu, Zheng Yuan, Jun Xia, Shengxuan Luo, Huaiyuan Ying, Sihang Zeng, Jingyi Ren, Hongyi Yuan, Zhengyun Zhao, Yucong Lin, Keming Lu, Jing Wang, Yutao Xie, Heung-Yeung Shum, “BIOS: An Algorithmically Generated Biomedical Knowledge Graph”, 2022. Preprint. (paper)
• Haolin Zhang, Maokun Li, Fan Yang, Shenheng Xu, Yan Yin, Hongyu Zhou, Yubo Yang, Sihang Zeng, Jianchong Shao, “A Feasibility Study of 2-D Microwave Thorax Imaging Based on the Supervised Descent Method”, 2021, Electronics. (paper)