Jean-Marc Odobez

EPFL STI IEM LIDIAP
ELD 241 (Bâtiment ELD)
Station 11
CH-1015 Lausanne

EPFLSTISTI-SELSEL-ENS

Expertise

Computer Vision, machine Learning (Bayesian models, deep learning), multimodal processing.
Activity analysis, human behavior understanding, human communication, interaction modeling
Dr Jean-Marc Odobez (Msc 1990, PhD 1994) received his Ph.D degree from Rennes University in 1994 for his PhD dissertation done at INRIA. After 5 years as an assistant professor at the University du Maine, France, he decided to join Idiap, where he is now the Head of the Perception & Activity Understanding Group and adjunct faculty at EPFL in the school of engineering and a member of the Electrical Engineering Doctoral committee (EDEE).
His research interests are the design of multimodal perception systems rooted in computer vision, statistical machine learning and deep learning, or social sciences, for activity and behavior recognition, human-human or human-robot interaction modeling and understanding. Application domains include human health assessment, social robotics, or media content analysis. He has published more than 50 journals and 160 conference refereed papers in his research field. He has been the principal investigator of more than 16 European and Swiss projects, and has worked on 10 tech transfer projects with SMEs. He holds several patents in computer vision, and is the cofounder of Klewel SA (www.klewel.ch) and Eyeware SA (eyeware.tech), a tech company in eye tracking and attention modeling. He is an IEEE member and associate editor of the Machine Vision and Application journal. He regularly serves as area chair for the ICMI, ICCV, CVPR or ECCV conferences.

Education

PhD

| Computer Science

1994 – 1994 Rennes I University

Engineering Degree

|

1990 – 1990 ENST Bretagne (Ecole Nationale d'Ing�nieur des T�l�coms de Bretagne)

Infoscience

Teaching & PhD

PhD Students

Vivek Samir Gupte, Yesmine Abdennadher, Samy Tafasca, Shalutha Navindu Rajapakshe Rajapakshe Mudiyanselage, Gökhan Özbulak, Karl El Hajal, Hasindri Sankalpana Watawana, Mingchi Hou, Pierre François Marie Vuillecard, João Pedro Gandarela de Souza, Anirban Mukherjee, Elija Maria Vida, Nawal Haidar, Mojtaba Nafez

Past EPFL PhD Students

Jagannadan Varadarajan, Alexandre Heili, Samira Sheikhi, Kenneth Alberto Funes Mora, Do Hoang Nam Le, Christian Jaques, Yu Yu, Olivia Mariani, Rémy Alain Siegfried, Angel Noe Martinez Gonzalez, Weipeng He, Thibaut Antoine Kulak, Teguh Santoso Lembono, Hakan Girgin, Enno Hermann, Julian David Fritsch, Alejandro Ramírez Atrio, Alexandre Samuel Philippe Bittar, Neha Tarigopula, Anshul Gupta, Eklavya Sarkar, Roberto Boghetti

Past EPFL PhD Students as codirector

Guillaume Lathoud, Pedro Manuel Da Silva Quelhas, Silèye Oumar Ba, Jagannadan Varadarajan, Edgar Roman Rangel, Alexandre Heili, Samira Sheikhi, Kenneth Alberto Funes Mora, Gülcan Can

Courses

Machine Learning for Engineers

EE-613

The objective of this course is to give an overview of machine learning techniques used for real-world applications, and to teach how to implement and use them in practice. Laboratories will be done in python using jupyter notebooks.

Perception and learning from multimodal sensors

EE-623

The course will cover different aspects of multimodal processing (complementarity vs redundancy; alignment and synchrony; fusion), with an emphasis on the analysis of people, behaviors and interactions from multimodal sensor, using statistical models and deep learning as main modeling tools.