Prof. Volkan Cevher

Research Interests:

  • Machine Learning
  • Optimization
  • Signal Processing
  • Information Theory

Biography

Volkan Cevher received the B.Sc. (valedictorian) in electrical engineering from Bilkent University in Ankara, Turkey, in 1999 and the Ph.D. in electrical and computer engineering from the Georgia Institute of Technology in Atlanta, GA in 2005. He was a Research Scientist with the University of Maryland, College Park, from 2006-2007 and also with Rice University in Houston, TX, from 2008-2009. He was also a Faculty Fellow in the Electrical and Computer Engineering Department at Rice University from 2010-2020. Currently, he is an Associate Professor at the Swiss Federal Institute of Technology Lausanne and an Amazon Scholar. His research interests include machine learning, optimization theory and methods, and automated control. Dr. Cevher is an IEEE Fellow (’24), an ELLIS fellow, and was the recipient of the ICML AdvML Best Paper Award in 2023, Google Faculty Research award in 2018, the IEEE Signal Processing Society Best Paper Award in 2016, a Best Paper Award at CAMSAP in 2015, a Best Paper Award at SPARS in 2009, and an ERC CG in 2016 as well as an ERC StG in 2011.

Publications (most recent)

Learning to Remove Cuts in Integer Linear Programming

P. Puigdemont; E. P. Skoulakis; G. Chrysos; V. Cevher 

2024. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, July 21-27, 2024.

Graph generative deep learning models with an application to circuit topologies

I. Krawczuk / V. Cevher; Y. Leblebici (Dir.)  

Lausanne, EPFL, 2024. 

Improving SAM Requires Rethinking its Optimization Formulation

W. Xie; F. Latorre; K. Antonakopoulos; T. M. Pethick; V. Cevher 

2024. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, July 21-27, 2024.

Robust NAS under adversarial training: benchmark, theory, and beyond

Y. Wu; F. Liu; C-J. Simon-Gabriel; G. Chrysos; V. Cevher 

2024. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.

High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization

Y. Chen; F. Liu; T. Suzuki; V. Cevher 

2024. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.

Contact

e-mail address: [email protected]


telephone: 0041 21 6930111


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