VG Vinod Vydiswaran, PhD
Associate Professor of Learning Health Sciences, Medical School
Associate Professor of Information, School of Information
[email protected]
Available to mentor
VG Vinod Vydiswaran, PhD
Associate Professor
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Qualifications
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Research FellowUniversity of Michigan, School of Information, Ann Arbor, MI, United States
2013 - 2015
Postdoctoral Research
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Postdoctoral ResearcherUniversity of Illinois, Beckman Institute, Urbana, United States
2013 - 2013
Postdoctoral Research
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Master of Technology, Information TechnologyIndian Institute of Technology Bombay, Mumbai, India
2002 - 2004
Center Memberships
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Center MemberCenter for Computational Medicine and Bioinformatics
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Center MemberAI and Digital Health Innovation
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Center MemberInstitute for Healthcare Policy and Innovation
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Center Membere-Health and Artificial Intelligence Initiative
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Center MemberCenter for Global Health Equity
Recent Publications
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Vydiswaran VGV. 2026 Jun 17;PresentationInvited panelist in the Workshop on Artificial Intelligence and the Medical Record in the Context of Social Security Disability Evaluations in the session on Leadership Roundtable
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Vydiswaran VGV. 2026 Jun 17;PatentMethods and systems for coupled agentic reinforcement learning
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Pandian B, Vandervest J, Mentz G, Varghese J, Steadman SD, Kheterpal S, Makar M, Vydiswaran VGV, Burns ML. Scientific Reports, 2025 Dec 1; 15 (1):Proceeding / Abstract / PosterGeneralizing machine learning models from clinical free text
DOI:10.1038/s41598-025-17197-6 PMID: 40866580 -
Ju X, Solka J, Weber K, Vydiswaran VV, Lin LA, Bonar EE, Fernandez AC. Drug and Alcohol Dependence, 2025 Dec 1; 277:Journal ArticleUnhealthy alcohol use detection in electronic health records: A comparative study using natural language processing
DOI:10.1016/j.drugalcdep.2025.112920 PMID: 41109081 -
Pandian B, Vandervest J, Mentz G, Varghese J, Steadman SD, Kheterpal S, Makar M, Vydiswaran VGV, Burns ML. Sci Rep, 2025 Aug 28; 15 (1): 31668Journal ArticleGeneralizing machine learning models from clinical free text.
DOI:10.1038/s41598-025-17197-6 PMID: PMC12391454 -
Han P, Zhang G, Vydiswaran VGV. Studies in Health Technology and Informatics, 2025 Aug 7; 329: 891 - 895.ChapterCorrecting Performance Metrics Bias During Generalization from Biased Samples to Populations
DOI:10.3233/SHTI250968 PMID: 40775986 -
Zhang Z, Zocher H, Rosen B, Covington E, Dess R, Evans J, Jackson W, Lawrence T, Matuszak M, Piatt G, Vydiswaran VGV, Mayo C. Clinical Cancer Research, 2025 Jul 21;Journal ArticleLeveraging Standardized Data Sources and Natural Language Inference Models to Extract Prostate Cancer Diagnosis and Staging at Scale from Clinical Notes
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Goodspeed R, Yuan M, Bhogal AN-B, Vydiswaran VV, Romero D, Willis M, Veinot T. 2025 Jun 1; SocArXiv,PreprintComparing methods for determining home and work locations from geotagged social media data
DOI:10.31235/osf.io/g7c4p_v2
Featured News & Stories
Department News
Vinod Vydiswaran Appointed Director of HILS Graduate Programs
DLHS Chair, Dr. Gretchen Piatt announced the appointment of Dr. Vinod Vydiswaran as the new Director of the Health Infrastructures and Learning Systems (HILS) MS and PhD programs, effective July 1, 2025.
Department News
HILS PhD student presents at Malta workshop on challenges facing patient de-identification systems
The Department of Learning Health Sciences and the Health Infrastructures and Learning Systems (HILS) team congratulates HILS PhD student, Dalton Simancek, MSI for his recent presentation at the 2024 Workshop on Computational Approaches to Language Data Pseudonymization (CALD-pseudo 2024) in St Julian’s, Malta.
Department News
DLHS awarded $5 million federal grant to train Learning Health System Scientists
The Department of Learning Health Sciences (DLHS) at the University of Michigan Medical School received a $5 million, five-year grant to apply innovative methods to improve health, healthcare, and health equity.
Health Lab
Dr. Vydiswaran’s Michigan Answer: Better outcomes through big data
Nearly all of us engage with some form of social media every day. But what if the true power of social media wasn’t found in a like, tweet or follow? For an emerging field of research taking place at Michigan Medicine, it’s the data inside social media that may have the power to give patients bigger answers and better outcomes.