Portrait of Dr. Vipul Garg

Dr. Vipul Garg

  • Assistant Professor at Department of Management, McCoy College of Business

Biography

I am an Assistant Professor of Supply Chain Management in the Department of Management at the McCoy College of Business, Texas State University. I hold a Ph.D. in Logistics Systems from the University of North Texas, an MS in Data Science, and a BS in Computer Science Engineering. Before academia, I spent 5 years as a Data Scientist and Product Manager building data and machine learning solutions for global clients.

Research Interests

My research covers two areas: how firms and consumers adopt technologies such as drones, artificial intelligence, and collaborative robotics, and how the design of safety regulations and reporting requirements shapes operational risk in trucking, warehousing, and production. The work sits at the intersection of operations, public policy, and cognitive science, and I collaborate with researchers in psychology, neuroscience, engineering, and public health. I have published 16 journal articles in outlets including Transportation Research Part E, Transportation Research Part D, and the International Journal of Physical Distribution & Logistics Management.

As Principal Investigator on four grants, I have built a research infrastructure that supports work well outside supply chain management. One award funded an EEG and eye-tracking study of forklift operators, measuring how cognitive load and production quotas affect worker safety and turnover. Another funded international firm-level panel dataset is now available to faculty across the college. I also developed an NSF proposal on privacy-preserving encryption for secure data sharing in U.S. port operations, joining cryptography and operations research.

Teaching Interests

Undergraduate and MBA: Operations Management; Supply Chain Management; Purchasing and Materials Management; Transportation and Logistics; Supply Chain Analytics

Doctoral: Research Methods; Seminar in Supply Chain and Operations; Technology Management in Operations