Dr. Uta Mohring is a postdoctoral researcher at the Rotman School of Management, University of Toronto, Canada. She received her doctoral degree from the Karlsruhe Institute of Technology (KIT), Germany, in 2022.
Her research is at the interface between management science, industrial engineering, and data science and focuses on prescriptive models for decision-making in manufacturing and service operations management. Within these fields, her research interests are specifically on resource synchronization and allocation problems under uncertainty and sharing economy applications, motivated by the ambition to derive innovative solutions for the design and control of future manufacturing and logistics systems and logistics and mobility networks.
In her research, she applies a broad range of mostly quantitative methods from the fields of operations research and business analytics including, specifically, stochastic, data-driven, game-theoretical, and simulation-based modeling and optimization techniques.
Her profile is distinguished by her substantial international research experience and network, her interdisciplinary research at the interface between management science, industrial engineering, and data science, and her strong experience in third-party funding.
Her research is at the interface between management science, industrial engineering, and data science and focuses on prescriptive models for decision-making in manufacturing and service operations management. Within these fields, her research interests are specifically on resource synchronization and allocation problems under uncertainty and sharing economy applications, motivated by the ambition to derive innovative solutions for the design and control of future manufacturing and logistics systems and logistics and mobility networks.
In her research, she applies a broad range of mostly quantitative methods from the fields of operations research and business analytics including, specifically, stochastic, data-driven, game-theoretical, and simulation-based modeling and optimization techniques.
Her profile is distinguished by her substantial international research experience and network, her interdisciplinary research at the interface between management science, industrial engineering, and data science, and her strong experience in third-party funding.
Techniques/Methodologies (alphabetical order)
Analytics, data-driven modeling, game theory, machine learning, network flow theory, optimization, queueing theory, simulation, statistics, stochastic modeling
Applications (alphabetical order)
Circular economy, demand management, e-commerce, last-mile logistics, manufacturing, platform economics, platform operations, production logistics, retail logistics, revenue management and pricing, shared mobility, sharing economy, supply chain management, sustainability, urban logistics, urban mobility, warehouse operations
Circular economy, demand management, e-commerce, last-mile logistics, manufacturing, platform economics, platform operations, production logistics, retail logistics, revenue management and pricing, shared mobility, sharing economy, supply chain management, sustainability, urban logistics, urban mobility, warehouse operations
