Emma Frejinger
Education
Ph.D., mathematics, École Polytechnique Fédérale de Lausanne; M.Sc., industrial engineering and management, Linköping University
Summary of Experience
Professor Frejinger is an expert in data-driven methods for solving large-scale decision-making problems under uncertainty. Her research, situated within the broad field of AI, focuses on developing mathematical models and algorithms that integrate techniques from econometrics, machine learning, and operations research. Her work has practical applications in areas such as transportation and supply chain management, and addresses challenges that include demand forecasting, pricing, service design, and scheduling. In Professor Frejinger’s deposition testimony and case work, she has drawn on practical and technical experience that includes years spent conducting research and developing bespoke production-grade AI solutions. Professor Frejinger serves as the Canada Research Chair in Data-Driven Optimization for Transportation for the Government of Canada and as the Chair in Optimization of Railway Operations for the Canadian National Railway Company. She is also a member of the Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation, a Canadian interdisciplinary research center. Professor Frejinger is an associate editor of Transportation Science and the INFORMS Journal on Computing. In the AI space, she has served as a scientific advisor to IVADO Labs, an AI solutions provider; as an associate academic member of Mila, an AI research institute; and as a founding fellow of AI Sweden, the Swedish national center for applied AI. Professor Frejinger’s work has received several international awards, including the Transportation Science and Logistics Society’s Dissertation Prize, presented by the Institute for Operations Research and the Management Sciences.