Volkan Cevher

Volkan Cevher is an Associate Professor at the Swiss Federal Institute of Technology Lausanne (EPFL), where he leads the Laboratory for Information and Inference Systems (LIONS). He also serves as an Amazon Scholar and previously held positions as a Research Scientist at the University of Maryland (2006-2007) and Rice University (2008-2009), as well as a Faculty Fellow at Rice University (2010-2020).

Dr. Cevher received his B.Sc. (valedictorian) in electrical engineering from Bilkent University in Ankara, Turkey, in 1999 and his Ph.D. in electrical and computer engineering from the Georgia Institute of Technology in 2005.

His research spans machine learning, optimization theory, signal processing, and their applications. He focuses on developing theoretically grounded algorithms for robust machine learning, with particular emphasis on non-convex optimization, adversarial training, and distributed learning. His work addresses fundamental challenges in optimization landscapes for neural networks and min-max problems like GANs and robust reinforcement learning.

Dr. Cevher's recent publications demonstrate strong trends in optimization for machine learning, with significant contributions to adversarial robustness, federated learning, and efficient training methods. His work bridges theoretical foundations with practical applications across multiple domains including NLP, computer vision, and reinforcement learning.

Dr. Cevher has received numerous prestigious awards including:

• IEEE Fellow (2024)
• ELLIS fellow
• ICML AdvML Best Paper Award (2023)
• Google Faculty Research award (2018)
• IEEE Signal Processing Society Best Paper Award (2016)
• ERC Consolidator Grant (2016)
• ERC Starting Grant (2011)

As head of the Laboratory for Information and Inference Systems at EPFL, Dr. Cevher leads a research group focused on advancing the theoretical foundations of machine learning and optimization. His lab has secured significant funding through competitive grants including multiple ERC grants. He actively mentors PhD students and postdoctoral researchers, with many of his advisees going on to successful careers in academia and industry.

The Laboratory for Information and Inference Systems (LIONS) at EPFL is a leading research group in optimization and machine learning, known for developing theoretically sound algorithms with practical impact. The lab collaborates extensively with industry partners and other academic institutions worldwide.