Anh T. NinhView profile
Associate Professor
Anh T. Ninh is an Associate Professor in the Department of Mathematics at William & Mary, where he also contributes to the M.S. program in Computational Operations Research within the Department of Computer Science. His academic work bridges mathematics, computer science, and healthcare applications, with a strong focus on optimization and machine learning. Research Interests: His primary research areas include optimization under uncertainty, machine learning, and their applications in healthcare systems, particularly in clinical trial design and pharmaceutical supply chain management. He develops advanced mathematical models to improve decision-making under uncertainty in complex operational environments. Publication Trends: His recent publications reflect a consistent focus on integrating stochastic and robust optimization with real-world healthcare logistics, clinical operations, and pharmaceutical planning. The works demonstrate a strong interdisciplinary approach, combining operations research, data science, and domain-specific knowledge to solve critical problems in health systems. Scientific Awards & Recognition: While no specific awards are listed in the provided text, his research is supported by the Bill & Melinda Gates Foundation, indicating significant recognition and impact in the field. He has also collaborated with major pharmaceutical companies such as Lifecell (now Abbvie), Sandoz, and IntegriChain, highlighting the practical relevance of his work. Advising and Grants: Dr. Ninh advises students through the Computational Operations Research program and leads externally funded research, including an active project on site selection funded by the Bill & Melinda Gates Foundation. His work bridges academia and industry, contributing to both theoretical advances and practical implementations in healthcare operations. Labs and Research Teams: While no formal lab name is mentioned, Dr. Ninh leads a research group focused on computational optimization and machine learning applications in healthcare. His team likely includes graduate students and collaborators from both mathematics and computer science, working on projects related to supply chain resilience, clinical trial efficiency, and data-driven healthcare decision-making.





