معرفی
Fredrik D. Johansson is an Associate Professor of Computer Science & Engineering at Chalmers University of Technology in Sweden, where he serves as Principal Investigator for the Healthy AI Lab. His academic career bridges theoretical machine learning with practical healthcare applications, focusing on causal inference methodologies for real-world decision making.
His research interests center on causal inference in machine learning and decision-making with healthcare applications. Johansson's work spans multiple subfields including treatment effect estimation, missing data handling, reinforcement learning for healthcare, and Alzheimer's disease simulation. His research group develops both theoretical frameworks and practical tools for causal machine learning.
Analysis of his recent publications reveals a strong emphasis on causal inference methodology with increasing healthcare applications, particularly in Alzheimer's disease research and treatment effect heterogeneity. His work consistently appears in top-tier machine learning venues including NeurIPS, ICML, AISTATS, and JMLR, demonstrating both theoretical rigor and practical relevance to healthcare decision making.
As an academic advisor, Johansson currently supervises seven PhD students: Herman Bergström, Alessandro Margueritte, Ahmet Balcioglu, Adam Breitholtz, Newton Mwai Kinyanjui, Anton Matsson, and Lena Stempfle, indicating an active and growing research group.
He leads the Healthy AI Lab at Chalmers University of Technology, which focuses on developing machine learning methods for healthcare applications with particular emphasis on causal inference. The lab has produced numerous software tools including Counterfactual Regression, Matching Kernels, and DLOREAN, along with datasets like IHDP-100, Jobs-Binary, and ADCB that have become standard benchmarks in the causal inference community.
