معرفی
Michael U. Gutmann is a Senior Lecturer in Machine Learning at the School of Informatics, University of Edinburgh, and a member of the Institute for Adaptive and Neural Computation. His research lies at the intersection of machine learning, statistics, and scientific applications, with a focus on developing inference methods for complex and implicit models.
Education:
- PhD in Computational Neuroscience, University of Tokyo
- MSc in Engineering and Applied Mathematics, Swiss Federal Institute of Technology (ETH) Zurich
- MSc, Ecole Centrale Paris
His primary research interests include Bayesian inference, likelihood-free inference, optimal experimental design, unsupervised learning, and applications in computational biology and neuroscience. He is best known for introducing Noise-Contrastive Estimation (NCE), a foundational technique for training unnormalized statistical models. His recent work spans variational inference, density ratio estimation, flow models for missing data, and AI-driven experimental design in behavioral and biological sciences.
His publications, including in NeurIPS, ICML, JMLR, and eLife, demonstrate a strong emphasis on methodological innovation for scientific discovery. He has contributed to open-source tools such as ELFI (Engine for Likelihood-Free Inference) and developed practical implementations of robust inference algorithms.
Scientific Awards:
- No specific awards listed in the provided texts.
Michael Gutmann actively supervises students and collaborates with leading researchers in machine learning and computational biology. He has secured research funding from EPSRC and BBSRC for projects in generative modeling and infectious disease epidemiology. He teaches advanced courses such as Probabilistic Modelling and Reasoning and Data Mining, reflecting his deep engagement with both theoretical and applied aspects of machine learning.
Labs and Research Groups:
- Institute for Adaptive and Neural Computation (ANC), University of Edinburgh
- Former affiliations with Department of Mathematics and Statistics and Department of Computer Science at the University of Helsinki and Aalto University
