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Kun-Hsing Yu, M.D., Ph.D.

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Biography
Stanford University, Stanford, CAPh.D.09/2016Biomedical Informatics
Stanford University, Stanford, CAPh.D. Minor09/2016Computer Science
National Taiwan University, Taipei, TaiwanM.D.06/2011Medicine
2024
Director’s Award
2024
Dean’s Innovation Award
2023
Career Development Award
2022 - 2022
Google Research Scholar Award
2021
National Institutes of Health (NIH) Maximizing Investigators' Research Award
2020 - 2020
Blavatnik Center for Computational Biomedicine Award
2018 - 2019
Schlager Family Award for Early Stage Digital Health Innovations
2017 - 2019
Harvard Data Science Fellowship
2017 - 2017
Pacific Symposium on Biocomputing (PSB) Rigorous Secondary Data Analysis Award
2015 - 2016
Howard Hughes Medical Institute (HHMI) Fellowship
2012 - 2016
Winston Chen Stanford Graduate Fellow
2010 - 2011
Best Intern Award, National Taiwan University Hospital

Overview
Kun-Hsing "Kun" Yu received his PhD in Biomedical Informatics and PhD Minor in Computer Science from Stanford University, and he obtained his MD from National Taiwan University, Taiwan. His research focuses on the integration of quantitative histopathology image patterns with multi-omics (genomics, epigenomics, transcriptomics, and proteomics) profiles to advance cancer research and clinical practice. His team has developed fully-automated algorithms to analyze whole-slide histopathology images at scale, discovered the molecular mechanisms underpinning the microscopic phenotypes of tumor cells, and identified novel cellular morphologies for patient prognosis. His research interests include quantitative pathology, machine learning, and translational bioinformatics.

Research
The research activities and funding listed below are automatically derived from NIH ExPORTER and other sources, which might result in incorrect or missing items. Faculty can login to make corrections and additions.
  1. R01HL174679 (YU, KUN-HSING) Jul 1, 2024 - Jun 30, 2027
    NIH
    Mitigating Hematologic Adverse Events in Patients with Myeloid Malignancies: A Novel Causal Artificial Intelligence Approach
    Role: Principal Investigator
  2. R35GM142879 (YU, KUN-HSING) Sep 1, 2021 - Jun 30, 2026
    NIH
    Robust, Generalizable, and Fair Machine Learning Models for Biomedicine
    Role: Principal Investigator

Bibliographic
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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.