Mathieu Salzmann

EPFL SDSC
INN 218 (Bâtiment INN)
Station 14
1015 Lausanne

EPFL SDSC
INN 218 (Bâtiment INN)
Station 14
1015 Lausanne

EPFL SDSC
INN 218 (Bâtiment INN)
Station 14
1015 Lausanne

EPFL SDSC
INN 218 (Bâtiment INN)
Station 14
1015 Lausanne

EPFL SDSC
INN 218 (Bâtiment INN)
Station 14
1015 Lausanne

Expertise

Computer Vision
Machine Learning

Current work

My main interests are:
- Deep learning for 2D and 3D visual scene understanding
- Efficient and robust deep learning
- Domain adaptation and generalization
- Interpretable machine learning
Mathieu Salzmann is the Deputy Chief Data Scientist of the Swiss Data Science Center (SDSC) and a Senior Scientist and Lecturer at EPFL. Between May 2020 and February 2024, he was also a part-time Senior GNC Engineer at ClearSpace. Previously, between February 2012 and June 2015, he was a Senior Researcher and Research Leader in NICTA's computer vision research group. Prior to this, from Sept. 2010 to Jan 2012, he was a Research Assistant Professor at TTI-Chicago, and, from Feb. 2009 to Aug. 2010, a postdoctoral fellow at ICSI and EECS at UC Berkeley under the supervision of Prof. Trevor Darrell. He obtained his PhD in Jan. 2009 from EPFL under the supervision of Prof. Pascal Fua. Mathieu Salzmann's research lies at the intersection of machine learning and visual recognition. He has published over 100 articles at top-tier peer-reviewed machine learning and computer vision venues, including CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, IEEE TPAMI, IJCV, JMLR, and IEEE TNN-LS. He regularly acts as an Area Chair for these venues and is an editorial board member for IEEE TPAMI and TMLR.

News

- As of March 2024, I am the Deputy Chief Data Scientist of the Swiss Data Science Center (SDSC)
- 4 papers accepted to ECCV 2024
- 1 paper accepted (oral) to ACM MM 2024
- 1 paper accepted to BMVC 2024
- 1 paper accepted to ICML 2024
- 3 papers accepted to ICLR 2024
- 6 papers accepted to CVPR 2024
- Our work in collaboration with S. Süsstrunk and R. Baroni on comics reconfiguration was displayed at the EPFL Pavilion A
- 1 paper accepted to NeurIPS 2023
- 5 papers accepted to ICCV 2023
- 1 paper accepted to ICML 2023
- I am Area Chair for ICML 2023, CVPR 2023, ICCV 2023, NeurIPS 2023, AAAI 2024, ECCV 2024
- I am Action Editor for TMLR
- I am Associate Editor for IEEE TPAMI
- As of Sept 2019, I have a Courtesy Appointment with the EPFL College of Humanities

Teaching & PhD

PhD Students

Zhuoqian Yang, Haoqi Wang, Yann Bouquet, Tianzong Zhang, Malo Lucas Perez, Saqib Javed, Megh Shukla, Shuangqi Li, Liying Lu, Pierre Victor Ancey

Past EPFL PhD Students

Chen Zhao

Past EPFL PhD Students as codirector

Kaicheng Yu, Isinsu Katircioglu, Chen Liu, Jan Bednarík, Krishna Kanth Nakka, Shuxuan Guo, Vidit Vidit, Sena Kiciroglu, Krzysztof Maciej Lis, Deblina Bhattacharjee, Davydov Andrey

Courses

Introduction to machine learning

CS-233

Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented.