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 operations management, industrial engineering, and data and computer 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 sustainable and effective design and control of future manufacturing and supply chains and urban logistics and mobility systems.
In her research, she applies a broad range of mostly quantitative methods from the fields of management and computer science 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 computer science, and her strong experience in third-party funding.
Her research is at the interface between operations management, industrial engineering, and data and computer 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 sustainable and effective design and control of future manufacturing and supply chains and urban logistics and mobility systems.
In her research, she applies a broad range of mostly quantitative methods from the fields of management and computer science 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 computer science, and her strong experience in third-party funding.
Techniques/Methodologies (alphabetical order)
Analytics, conceptual modeling, data-driven modeling and optimization, game theory, machine learning, operations research, queueing theory, simulation, statistics, stochastic modeling and optimization
Applications (alphabetical order)
Circular economy, demand management, e-commerce, last-mile logistics, manufacturing, material handling, platform economics, platform operations, pricing, production logistics, retail logistics, revenue management, shared mobility, sharing economy, supply chain management, sustainability, urban logistics, urban mobility, warehouse operations
Circular economy, demand management, e-commerce, last-mile logistics, manufacturing, material handling, platform economics, platform operations, pricing, production logistics, retail logistics, revenue management, shared mobility, sharing economy, supply chain management, sustainability, urban logistics, urban mobility, warehouse operations
