Public Biography
Dr. Huan He is a Data Scientist in the Division of Hematology/Oncology, Department of Internal Medicine at Mayo Clinic in Arizona. His research lies at the intersection of visual analytics, agentic AI systems, and clinical informatics, focusing on developing human-in-the-loop AI applications to address complex challenges in biomedical research and oncology practice.
At Mayo Clinic, Dr. He leads the system architecture and visualization design for scalable clinical trial matching systems. His current research pioneeringly integrates Autonomous AI Agents with Visual Analytics to build Living Systematic Review systems, streamlining evidence synthesis and supporting clinical practice guidelines. His core research agenda centers on human-centered AI, enhancing human-in-the-loop interactions, clinical patient recruitment, and data standardization (such as OMOP CDM and UMLS) through interactive visual computing.
Prior to joining Mayo Clinic, Dr. He was a Research Scientist in the Section of Biomedical Informatics and Data Science at Yale University School of Medicine, where he led the development of several innovative visual analytics systems. His prior work includes MedViz, a platform leveraging LLMs and retrieval-augmented generation (RAG) for semantic exploration of biomedical literature, and CDEMapper, an LLM-assisted tool for streamlining NIH Common Data Element (CDE) mapping, alongside EHR-based cohort discovery tools.
Dr. He brings a deep background in software engineering, natural language processing (NLP), and biomedical data architectures. He is an active contributor to open-source healthcare tools and scientific software platforms. Beyond his primary work, Dr. He serves as the chair-elect of the AMIA Visual Analytics Working Group and sits on the ASCO clinical guideline panel. He is also a regular reviewer for top-tier venues including AMIA, IEEE VIS, JAMIA, JBI, and JMIR.
At Mayo Clinic, Dr. He leads the system architecture and visualization design for scalable clinical trial matching systems. His current research pioneeringly integrates Autonomous AI Agents with Visual Analytics to build Living Systematic Review systems, streamlining evidence synthesis and supporting clinical practice guidelines. His core research agenda centers on human-centered AI, enhancing human-in-the-loop interactions, clinical patient recruitment, and data standardization (such as OMOP CDM and UMLS) through interactive visual computing.
Prior to joining Mayo Clinic, Dr. He was a Research Scientist in the Section of Biomedical Informatics and Data Science at Yale University School of Medicine, where he led the development of several innovative visual analytics systems. His prior work includes MedViz, a platform leveraging LLMs and retrieval-augmented generation (RAG) for semantic exploration of biomedical literature, and CDEMapper, an LLM-assisted tool for streamlining NIH Common Data Element (CDE) mapping, alongside EHR-based cohort discovery tools.
Dr. He brings a deep background in software engineering, natural language processing (NLP), and biomedical data architectures. He is an active contributor to open-source healthcare tools and scientific software platforms. Beyond his primary work, Dr. He serves as the chair-elect of the AMIA Visual Analytics Working Group and sits on the ASCO clinical guideline panel. He is also a regular reviewer for top-tier venues including AMIA, IEEE VIS, JAMIA, JBI, and JMIR.
Affiliations
Visual Analytics
Working Group
Chair Elect
The mission is to promote the development and validation of new visual analytical techniques that can be used to address some of the fundamental data and informatics challenges evident in the healthcare domain
Learn more about this group