Brief Biosketch
Ruslan Salakhutdinov received his PhD in machine learning (computer science) from the University of Toronto in 2009. After spending two post-doctoral years at the Massachusetts Institute of Technology Artificial Intelligence Lab, he joined the University of Toronto as an Assistant Professor in the Department of Computer Science and Department of Statistics. In February of 2016, he joined the Machine Learning Department at Carnegie Mellon University.Ruslan's primary interests lie in deep learning, machine learning, and large-scale optimization. His main research goal is to understand the computational and statistical principles required for discovering structure in large amounts of data. He is an action editor of the Journal of Machine Learning Research and served on the senior programme committee of several learning conferences including NIPS and ICML. He is an Alfred P. Sloan Research Fellow, Microsoft Research Faculty Fellow, Canada Research Chair in Statistical Machine Learning, a recipient of the Early Researcher Award, Connaught New Researcher Award, Google Faculty Award, Nvidia's Pioneers of AI award, and is a Senior Fellow of the Canadian Institute for Advanced Research.
Academic History
-
Carnegie Mellon University (2016 -- present)
Associate Professor
Machine Learning Department
-
University of Toronto (2011 -- 2016)
Assistant Professor
Department of Computer Science and Department of Statistics
- Massachusetts Institute of Technology (2009 -- 2011)
Postdoctoral Associate
Department of Brain and Cognitive Sciences and Computer Science & AI Laboratory (CSAIL).
- University of Toronto (2005 -- 2009)
PhD, University of Toronto, Machine Learning.
Funding Sources
Alfred P. Sloan Foundation | Google Research | Microsoft Research | Samsung |
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Office of Naval Research | DARPA | Raytheon BBN Technologies | Canadian Institute for Advanced Research |
Grants, Scholarships and Fellowships
As a faculty member:
- Samsung, Deep Learning Grant, 2015-2017
- Raytheon BBN Technologies, Deep Learning for Video Analysis, 2014-2016
- Samsung, Deep Learning for Face Recognition, 2014-2015
- Google Faculty Award, 2014-2015
- ONR Grant, Deep Structured Learning for Scene Understanding, 2013-2017
- Microsoft Research Faculty Fellowship, 2013-2015
- Alfred P. Sloan Research Fellowship, 2013-2015
- Dean's Merit Award, 2012, 2013.
- Connaught New Researcher Award (2012 - 2014)
- Early Researcher Award (2012-2017)
- NSERC Individual Discovery Grant , along with NSERC Early Career Researcher Supplement (2012-2017)
- Canadian Institute for Advanced Research
(CIFAR) (2011 -- 2014),
Fellow of the Neural Computation and Adaptive Perception Program
As a postdoc:
- Natural Sciences and Engineering Research Council of Canada (NSERC):
Postdoctoral Fellowship (2009 -2011). -
The UK Engineering and Physical Sciences Research Council (2009 -- 2012)
Postdoctoral Fellowship in Theoretical Computer Science (Declined)
As a student:
- NSERC Canada Graduate Scholarship.
- Ontario Graduate Scholarship (Declined).
- Precarn Scholar, Canada.
Invited Conference/Research Workshop
- I am serving as a workshop chair for ICML 2016.
- I am serving as an Area Chair for ICML 2015, ICLR 2016, and NIPS 2016.
- I am serving as an Action Editor for JMLR, 2013-2016.
- I joining editorial board of JAIR, 2014-2017.
- I served as a Demonstration Chair for NIPS 2013.
- I served as an Area Chair for the ICML 2013 program committee.
-
I served
as an Area Chair for the
NIPS 2012 program committee.
-
I served
as a Workshop Chair for the
UAI 2012.
- I served
as an Area Chair for the
ICML 2012
program committee.
- I served as an Area Chair for the NIPS 2011 program committee.
- I served as an ICML 2011 Area Chair for Deep Learning, Optimization Algorithms, Recommendation and Matrix Factorization.
Senior Program Committee
-
I co-organized ICML 2013 workshop on
Inferning: Interactions between Inference and Learning.
- Quoc V. Le,
Marc'Aurelio Ranzato,
Andrew Ng,
Josh Tenenbaum,
and I are organizing
a NIPS (2011) workshop on
Challenges in Learning Hierarchical Models: Transfer Learning and
Optimization.
- Together with Ryan Adams, Josh Tenenbaum, Zoubin Ghahramani, and Tom Griffiths, I organized
a NIPS workshop on
Transfer Learning Via Rich Generative Models
NIPS 2010.
-
Amir Globerson, David Sontag, and I organized a workshop on
Approximate Learning of Large Scale Graphical Models:
Theory and Applications,
NIPS 2009.
-
Together with Kai Yu, Yann LeCun, Geoffrey Hinton, and Yoshua Bengio,
I organized a workshop on
Learning Feature Hierarchies,
ICML 2009.
- I was co-organizing Deep Learning Workshop: Foundations and Future Directions, NIPS 2007.