معرفی
Fredrik Lindsten is a Senior Associate Professor in Machine Learning and Head of the Division of Statistics and Machine Learning at Linköping University's Department of Computer and Information Science (IDA). His research focuses on statistical machine learning, emphasizing probabilistic modeling and uncertainty quantification in methods such as approximate Bayesian inference, representation learning, and graph-based approaches. Applications span weather forecasting, materials science, biochemistry, and automotive industry challenges.
- Education: MSc (2008), PhD (2013) in Automatic Control from Linköping University; Postdoctoral roles at University of Cambridge, UC Berkeley, and University of Oxford.
- Affiliations: WASP (Wallenberg AI, Autonomous Systems and Software Program), ELLIIT (Lab for Information and Communication Technology).
Research Interests: Lindsten’s work bridges statistical methodology and machine learning, particularly in quantifying uncertainty in predictions. His team explores method development across diverse applications, including spatio-temporal models and graph-based techniques. Recent projects include probabilistic weather forecasting with graph neural networks and cryo-EM reconstruction techniques.
Publications: Over 25+ peer-reviewed articles, with recent highlights in Nature Methods, NeurIPS, and Physical Review Materials, focusing on Bayesian methods, generative models, and computational statistics.
- Awards: Ingvar Carlsson Award (Swedish Foundation for Strategic Research), Benzelius Award (Royal Society of Sciences in Uppsala).
- Grants & Teams: Supervises 7+ PhD students; active in collaborative projects funded by WASP, ELLIIT, and VR (Swedish Research Council).
Labs/Teams: Leads the Division of Statistics and Machine Learning (STIMA) at IDA, fostering interdisciplinary research in probabilistic machine learning.
