About me

• PhD student at Department of Biomedical Informatics and Medical Education, University of Washington
• Research Interests: Multimodal Longitudinal Electronic Health Record; LLM for Scientific Discovery; Trustworthy AI
• Other Interests: Skiing, Hiking, Traveling, Photography
• I’m open to research internship opportunities in summer 2025 and 2026.

Education

• Ph.D. student in Biomedical Informatics, 2023—
  • University of Washington, United States
  • Advisor: Ruth Etzioni (Professor), Meliha Yetisgen (Professor), Steven Zeliadt (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

• 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.
• Mar 2025: I attend ICIMH and present the how CIH therapies and Whole Health coaching impact tobacco cessation. Great experience!
• 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.
• Nov 2024: I attend AMIA and meet a lot of great people.
• Oct 2024: I present the poster “Large Language Models as Biomedical Hypothesis Generators: A Comprehensive Evaluation” at COLM 2024.
• 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.
• Jul 2024: I serve as a reviewer for JMIR
• Jun 2024: I serve as a reviewer for ICML 2024 Workshop AI4Science.
• 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.
• Dec 2023: Our paper “CoRTEx: Contrastive Learning for Representing Terms via Explanations with Applications on Constructing Biomedical Knowledge Graphs” is available on arXiv.
• Oct 2023: Our paper “Large Language Models are Zero Shot Hypothesis Proposers” is accepted by Instruction Workshop @ NeurIPS 2023 as a poster presentation.
• Oct 2023: I serve as a reviewer for Instruction Workshop @ NeurIPS 2023.
• 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’m graduated 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 contribution)

• 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)