معرفی
Murat Erdogdu is an Assistant Professor at the University of Toronto, jointly appointed in the Department of Computer Science and Department of Statistical Sciences. He is also a faculty member at the Vector Institute and holds the CIFAR Chair in Artificial Intelligence.
- PhD in Statistics, Stanford University (advised by Mohsen Bayati and Andrea Montanari)
- MSc in Computer Science, Stanford University
- BSc in Electrical Engineering and Mathematics, Bogazici University
His research focuses on machine learning theory, high-dimensional statistics, and optimization. He has contributed to understanding gradient-based algorithms, sampling methods, and feature learning in structured data.
Recent publications address problems in:
- Heavy-tailed sampling
- Mean-field Langevin dynamics
- Robust feature learning
- Minimax regression
- Stochastic optimization under infinite noise
Scientific Awards:
- CIFAR Chair in Artificial Intelligence
- ICLR 2023 Spotlight
- NeurIPS 2019 & 2021 Spotlights
He teaches graduate courses like STA 414/2104 (Statistical Methods for Machine Learning II) and STA 4273 (Modern Learning Theory), emphasizing probabilistic modeling and theoretical analysis.
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