Phone:

(317) 278-7722

Email:

kunhuang@iu.edu

Departments:

Biostatistics and Health Data Science

Additional Appointments:

Chair for Genomic Data Science, IUSM Precision Health Initiative

Director, Data Science and Informatics, IU Precision Health Initiative

Associate Director of Data Science, IU Simon Comprehensive Cancer Center

Investigator, Regenstrief Institute

Degrees:

PhD, Electrical and Computer Engineering, University of Illinois at Urbana-Champaign

MS, Molecular and Systems Physiology, University of Illinois at Urbana-Champaign

MS, Mathematics, University of Illinois at Urbana-Champaign

BS, Biology, Tsinghua University, Beijing, China

Resume/CV

Biography

Dr. Kun Huang is an internationally recognized leader in bioinformatics and computational pathology. He joined the Indiana University School of Medicine (IUSM) in 2017 as the Director of Data Science and Informatics for the Precision Health Initiative (PHI) and the IUSM PHI Endowed Chair in Genomic Data Science. Currently Dr. Huang is the Chair of the Department of Biostatistics and Health Data Science in the IU School of Medicine and the Fairbanks School of Public Health and Associate Director of Data Science for the IU Simon Comprehensive Cancer Center.

His research interests lie in translational bioinformatics, computational pathology, medical imaging, computational biology, integrative genomics tools for precision health, computer vision, and machine learning with applications in cancers and Alzheimer’s disease. He is focused on translating informatics tools to improve clinical practice and accelerate scientific discovery and believes the Precision Health Initiative is an unprecedented opportunity to accomplish just that.

In addition to his other appointments, Dr. Huang is an Investigator at the Regenstrief Institute’s Clem MacDonald Center for Biomedical Informatics, a senior investigator for the Center for Computational Biology and Bioinformatics and an Adjunct Professor in the Luddy School of Informatics, Computing, and Engineering. He is an elected Fellow of the American Institute of Biological and Medical Engineering (AIMBE).

Research Interests

• Translational informatics and integrative genomics tools for precision medicine
• Algorithms, software, and pipelines for computational pathology and bioimage informatics
• Data science theory and methods for mining and visualizing big and complex biomedical data
• Theory and algorithms for computer vision, machine learning, and AI

Selected Publications

• Johnson T, Yu CY, Huang Z, Xu S, Wang T, Dong C, Shao W, Abu Zaid M, Huang X, Wang J, Bartlett C, Zhang Y, Walker B, Liu Y, Huang K*, Zhang J*. Diagnostic Evidence GAuge of Single cells (DEGAS): a flexible deep transfer learning framework for prioritizing cells in relation to disease, Genome Medicine, 14:11, 2022.
• Wang T, Shao W, Huang Z, Tang H, Zhang J, Ding Z*, Huang K*. MOGONET integrates multi-omics data using graph convolutional networks allowing patient classification and biomarker identification, Nature Communications, 12 (1): 3445, 2021.
• Sun L, Zhang J, Chen W, Chen Y, Zhang X, Yang M, Xiao M, Ma F, Yao Y, Ye M, Zhang Z, Chen K, Chen F, Ren Y, Ni S, Zhang X, Yan Z, Sun Z-R, Zhou H-M, Yang H, Xie S, Haque ME, Huang K*, Yang Y*. Attenuation of epigenetic regulator SMARCA4 and ERK-ETS signaling suppresses aging-related dopaminergic degeneration. Aging Cell, 19(9): e13210, 2020. (* co-corresponding authors)
• Shao W, Wang T, Sun L, Dong T, Han Z, Huang Z, Zhang J, Zhang D, Huang K. Multi-task multi-modal learning for joint diagnosis and prognosis of human cancers. Medical Image Analysis, 65: 101795, 2020.
• Cheng J, Han Z, Mehra R, Shao W, Cheng M, Feng Q, Ni D*, Huang K*, Cheng L*, Zhang J*. Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma, Nature Communications, 11(1):1778, 2020. (* co-corresponding authors) PubMed PMID: 32286325; PubMed Central PMCID: PMC7156652.
• Wang T, Johnson T, Shao W, Zhang J*, Huang K*. BERMUDA: a novel deep transfer learning method for single-cell RNA sequencing batch correction reveals hidden high-resolution cellular subtypes, Genome Biology, 20(1): 165, 2019. PubMed PMID: 31405383; PubMed Central PMCID: PMC6691531.
• Shao W, Han Z, Cheng J, Cheng L, Wang T, Sun L, Lu Z, Zhang J, Zhang D, Huang K. Integrative analysis of pathological images and multi-dimensional genomic data for early-stage cancer prognosis, IEEE Transactions on Medical Imaging, 39(1): 99-110, 2019. PubMed PMID: 31170067.
• Johnson T, Wang T, Huang Z, Yu CY, Wu Y, Han Y, Zhang Y, Huang K*, Zhang J*., LAmbDA: label ambiguous domain adaptation dataset integration reduces batch effects and improves subtype detection, Bioinformatics, 35(22): 4696-4706, 2019. PubMed PMID: 31038669; PubMed Central PMCID: PMC6853662.
• Shi W, Xianyu A, Han Z*, Tang X, Li Z, Zhong H, Mao T, Huang K*, Shi S-H*. Ontogenetic establishment of order-specific nuclear organization in the mammalian thalamus. Accepted to Nature Neuroscience, 2017. (*co-corresponding authors)
• Cheng J*, Zhang J*, Han Y, Wang X, Ye X, Meng Y, Pawani A, Han Z, Feng Q, Huang K, Integrative analysis of histopathological images and genomic data for predicting clear cell renal cell carcinoma prognosis, Cancer Research, 77(21): e91-e100, 2017. (*co-first authors)

ORCID ID