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)

HeNCler: Node Clustering in Heterophilous Graphs via Learned Asymmetric Similarity

S. Achten; Z. Op de Beeck; F. Tonin; V. Cevher; J. A. Suykens 

2026. 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, 2025-09-09 – 2025-09-12. p. 55 – 68. DOI : 10.1007/978-3-032-04552-2_8.

Deep‐Learning‐Assisted SICM for Enhanced Real‐Time Imaging of Nanoscale Biological Dynamics

Z. Ayar; M. Penedo; B. Drake; J. Shi; S. M. Leitao et al. 

Small Methods. 2025. DOI : 10.1002/smtd.202501080.

On the Complexity of a Simple Primal-dual Coordinate Method

A. Alacaoglu; V. Cevher; S. J. Wright 

MATHEMATICAL PROGRAMMING. 2025. DOI : 10.1007/s10107-025-02247-8.

Accelerating Spectral Clustering under Fairness Constraints

F. Tonin; A. Lambert; J. Suykens; V. Cevher 

2025. Forty-Second International Conference on Machine Learning, Vancouver, Canada, 2025-07-13 – 2025-07-19.

Best of Both Worlds: Regret Minimization versus Minimax Play

A. Müller; J. Schneider; S. Skoulakis; L. Viano; V. Cevher 

2025. Forty-Second International Conference on Machine Learning, Vancouver, Canada, 2025-07-13 – 2025-07-19.

Continuous-Time Analysis of Heavy Ball Momentum in Min-Max Games

Y. Feng; K. Fujii; S. Skoulakis; X. Wang; V. Cevher 

2025. Forty-Second International Conference on Machine Learning, Vancouver, Canada, 2025-07-13 – 2025-07-19.

Generalization of Noisy SGD in Unbounded Non-convex Settings

L. Dadi; V. Cevher 

2025. Forty-Second International Conference on Machine Learning, Vancouver, Canada, 2025-07-13 – 2025-07-19.

IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic

S. Viel; L. Viano; V. Cevher 

2025. Forty-Second International Conference on Machine Learning, Vancouver, Canada, 2025-07-13 – 2025-07-19.

CHAMELEON: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning

W. Xie; F. Tonin; V. Cevher 

2025. Forty-Second International Conference on Machine Learning, Vancouver, Canada, 2025-07-13 – 2025-07-19.

Layer-wise Quantization for Quantized Optimistic Dual Averaging

A. Duc Nguyen; I. Markov; F. Z. Wu; A. Ramezani-Kebrya; K. Antonakopoulos et al. 

2025. Forty-Second International Conference on Machine Learning, Vancouver, Canada, 2025-07-13 – 2025-07-19.

Training Deep Learning Models with Norm-Constrained LMOs

T. Pethick; W. Xie; K. Antonakopoulos; Z. Zhu; A. Silveti-Falls et al. 

2025. Forty-Second International Conference on Machine Learning, Vancouver, Canada, 2025-07-13 – 2025-07-19.

Adaptive Bilevel Optimization

K. Antonakopoulos; S. Sabach; L. Viano; M. Hong; V. Cevher 

ACM / IMS Journal of Data Science. 2025. DOI : 10.1145/3728478.

Addressing Label Shift In Distributed Learning Via Entropy Regularization

Z. Wu; C. Choi; X. Cao; V. Cevher; A. Ramezani-Kebrya 

2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.

How Gradient Descent Balances Features: A Dynamical Analysis For Two-Layer Neural Networks

Z. Zhu; F. Liu; V. Cevher 

2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.

Efficient Interpolation Between Extragradient And Proximal Methods For Weak MVIS

T. Pethick; I. Mavrothalassitis; V. Cevher 

2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.

Faster Inference Of Flow-Based Generative Models Via Improved Data-Noise Coupling

A. Davtyan; L. T. Dadi; V. Cevher; P. Favaro 

2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.

Adversarial Training For Defense Against Label Poisoning Attacks

I. B. Melis; V. Cevher; M. Muehlebach 

2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.

Quantum-Peft: Ultra Parameter-Efficient Fine-Tuning

T. Koike-Akino; F. Tonin; Y. Wu; F. Z. Wu; L. Candogan et al. 

2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.

Certified Robustness Under Bounded Levenshtein Distance

E. Abad Rocamora; G. Chrysos; V. Cevher 

2025. The Thirteenth International Conference on Learning Representations, Singapore, 2025-04-24-2025-04-28.

Single-pass Detection of Jailbreaking Input in Large Language Models

L. Candogan; Y. Wu; E. Abad Rocamora; G. Chrysos; V. Cevher 

Transactions on Machine Learning Research. 2025. Vol. 02/2025.

Contact

e-mail address: Volkan Cevher


telephone: +41 21 6930111


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