Vikas Chowdhry is the Founder and CEO of TraumaCare.AI, where he is building AI-powered tools to help trauma and ICU teams improve outcomes for critically injured patients. He founded the company after spending two decades developing deep expertise in healthcare technology, clinical AI, and product leadership — skills he now applies to one of medicine's most time-critical domains.
Parkland Center for Clinical Innovation
Before founding TraumaCare.AI, Vikas was Chief Analytics and Information Officer at the Parkland Center for Clinical Innovation in Dallas. There, he led a team of data scientists, engineers, and clinicians building workflow-integrated AI solutions across chronic and acute care. His projects included a HIPAA-compliant cloud analytics platform, predictive models for trauma and sepsis, and a care coordination program for high-risk pregnant women in underserved Dallas communities — work that contributed to published research on the role of social determinants in maternal and pediatric health outcomes.
Epic Systems
Earlier, Vikas spent over a decade at Epic, where he bootstrapped the company's machine learning team and helped establish it as a leader in healthcare predictive analytics. He built the technical and legal frameworks for deploying models in clinical workflows and led development of Epic's population health platform, which now tracks over 130 million patients across 200+ health systems. His work there earned him leadership roles overseeing analytics, machine learning, acute care, radiology, and obstetrics product lines.
Education & Academic Roles
Vikas holds an MBA from Chicago Booth with concentrations in Finance, Entrepreneurship, and Strategy, an MS in Computer Science from the University of Illinois, and a BS in Computer Science from the University of Jodhpur, India. He is a Faculty Associate at UT Southwestern Medical Center, where he teaches in the Health Informatics graduate program, and Adjunct Faculty at SMU Cox School of Business.
Research
His research includes publications on scalable machine learning platforms for healthcare, deep learning approaches to predicting pediatric asthma emergencies, and external validation of mortality predictors in polytrauma patients (Journal of Surgical Research, 2024).