Kun-Hsing Yu

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Biography

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.

Education and Training

• M.D., Medicine
  National Taiwan University
• Ph.D., Biomedical Informatics
  Stanford University
• Ph.D. Minor, Computer Science
  Stanford University

Awards and Honors

• Dean’s Innovation Award, 2024
  Harvard Medical School
• Director’s Award, 2024
  Convergent Science Virtual Cancer Center (CSVCC)
• Career Development Award, 2023
  Department of Defense
• Google Research Scholar Award, 2022
• National Institutes of Health (NIH) Maximizing Investigators' Research Award, 2021
  National Institutes of Health (NIH)
• Blavatnik Center for Computational Biomedicine Award, 2020
• Schlager Family Award for Early Stage Digital Health Innovations, 2018 - 2019
  Brigham and Women's Hospital
• Harvard Data Science Fellowship, 2017 - 2019
  Harvard University
• Pacific Symposium on Biocomputing (PSB) Rigorous Secondary Data Analysis Award, 2017
  Pacific Symposium on Biocomputing (PSB)
• Howard Hughes Medical Institute (HHMI) Fellowship, 2015 - 2016
  Howard Hughes Medical Institute (HHMI)
• Winston Chen Stanford Graduate Fellow, 2012 - 2016
  Stanford University
• Best Intern Award, National Taiwan University Hospital, 2010 - 2011
  National Taiwan University Hospital

Publications

• Prognostic role of inflammatory diets in colorectal cancer overall and in strata of tumor-infiltrating lymphocyte levels.

  Ugai T, Liu L, Tabung FK, Hamada T, Langworthy BW, Akimoto N, Haruki K, Takashima Y, Okadome K, Kawamura H, Zhao M, Kahaki SMM, Glickman JN, Lennerz JK, Zhang X, Chan AT, Fuchs CS, Song M, Wang M, Yu KH, Giannakis M, Nowak JA, Meyerhardt JA, Wu K, Ogino S, Giovannucci EL. Clin Transl Med 2022 11

• Prediction of early-stage melanoma recurrence using clinical and histopathologic features.

  Wan G, Nguyen N, Liu F, DeSimone MS, Leung BW, Rajeh A, Collier MR, Choi MS, Amadife M, Tang K, Zhang S, Phillipps JS, Jairath R, Alexander NA, Hua Y, Jiao M, Chen W, Ho D, Duey S, Németh IB, Marko-Varga G, Valdés JG, Liu D, Boland GM, Gusev A, Sorger PK, Yu KH, Semenov YR. NPJ Precis Oncol 2022 Oct 31

• Association of Race and Socioeconomic Disadvantage With Missed Telemedicine Visits for Pediatric Patients During the COVID-19 Pandemic.

  Brociner E, Yu KH, Kohane IS, Crowley M. JAMA Pediatr 2022 09 01

• The impact of stage-related features in melanoma recurrence prediction: A machine learning approach.

  Wan G, Leung B, Nguyen N, DeSimone MS, Liu F, Choi MS, Ho D, Laucks V, Duey S, Sullivan RJ, Boland GM, LeBoeuf NR, Liu D, Gusev A, Kwatra SG, Sorger PK, Yu KH, Semenov YR. JAAD Int 2023

• Survival Prediction After Neurosurgical Resection of Brain Metastases: A Machine Learning Approach.

  Hulsbergen AFC, Lo YT, Awakimjan I, Kavouridis VK, Phillips JG, Smith TR, Verhoeff JJC, Yu KH, Broekman MLD, Arnaout O. Neurosurgery 2022 09 01