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Jan Kronqvist is an Associate Professor at the Royal Institute of Technology (KTH) in Sweden, specializing in Optimization and Systems Theory within the Department of Mathematics. He began his academic career as an Assistant Professor at KTH in 2021 after completing a two-year postdoctoral fellowship at Imperial College London as a Newton International Fellow. Jan earned his PhD from Åbo Akademi University in 2018, graduating with honors and receiving an award for his PhD thesis. During his doctoral studies, he spent six months as a visiting researcher at Carnegie Mellon University. Prior to joining KTH, he worked as a university teacher at Åbo Akademi in Process Systems Engineering. His research primarily focuses on mixed-integer optimization, where he develops algorithms and techniques to solve complex optimization problems, particularly in the context of AI and machine learning applications. He is known for developing the award-winning mixed-integer solver SHOT, recognized as the fastest convex MINLP solver according to extensive benchmarks. Jan actively organizes events such as the Stockholm Optimization Days and the Stockholm Global Optimization Workshop, and leads a research group at KTH that includes several PhD students and postdoctoral researchers, each contributing to various fields of optimization and machine learning.
Royal Institute of Technology • Stockholm, Sweden
Specializing in Optimization and Systems Theory.
Imperial College London •
Worked as a Newton International Fellow in the field of optimization.
Åbo Akademi University •
Taught courses in Process Systems Engineering.
Specific requirements apply to all departments. For Architecture, a portfolio is mandatory and submitted via a separate KTH system.