Murat Erdogdu
  • Assistant Professor in both Computer Science and Statistics, University of Toronto

    Faculty Member, Vector Institute

    Canada CIFAR Artificial Intelligence Chair

    Website | Google Scholar

Research Interests

  • Machine Learning: Graphical models, message passing algorithms
  • Optimization: Efficient algorithms for machine learning
  • Statistics: High-dimensional data analysis, regularization and shrinkage


With a background in engineering, Murat has a keen interest in applying theory to solve real-world problems. His primary interest is in designing optimization algorithms for machine learning models. Using efficient algorithms, model training time can be reduced significantly, allowing researchers to efficiently test and select the best model for the problem at hand, be it recommender systems or image denoising. Murat completed his PhD in the Department of Statistics at Stanford University. He holds a Master’s in Computer Science from Stanford and Bachelor’s degrees in Electrical Engineering and Mathematics from Bogazici University in Turkey. Murat is currently a postdoctoral researcher at Microsoft Research – New England. Murat regularly publishes at the top-rated machine learning conference NIPS, and has journal papers in the Annals of Statistics and JMLR.

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