Thomas Serre

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SUnS symposium

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Last update: Mon 25-May-2009

Curriculum vitae

 

Research interests

Biological vision, machine vision, computational models of cortex, scene understanding, object recognition, computational neuroscience, learning in cortex.

Education

Postdoctoral Associate.

MIT, McGovern Institute, Cambridge, MA.

since 05/06

PhD computational neuroscience.

MIT, Brain and Cog Sciences Dept, Cambridge, MA.

Advisor: Tomaso Poggio.

09/01-05/06

DEA (M.Sc.) in EECS.

Universite de Rennes, France.

09/99-10/00

Ingenieur des Telecommunications.

Ecole Nationale Superieure des Telecommunications de Bretagne, Brest, France (graduate).

09/97-10/00

Classes Preparatoires (BS) aux Grandes Ecoles P* (math and physics).

Lycee Pasteur, Neuilly, France (undergraduate)

09/95-09/97
Organization of meetings

SUnS - Scene Understanding Symposium. MIT, Cambridge, MA. Organizers: Aude Oliva, Thomas Serre, Antonio Torralba.

The symposium runs every year in early February. It features speakers from a variety of disciplines (neurophysiology, cognitive neuroscience, visual cognition, computational neuroscience and computer vision) who address a range of topics related to real world scene understanding and natural image processing, rapid image recognition, contextual effects on object recognition, the relationships between bottom-up and top-down processes of visual information, the role of attention in complex image recognition, among others. The goal of the symposium is to encourage exchanges between researchers of all fields of brain sciences in the burgeoning field of scene understanding.

Professional memberships
Cognitive Neuroscience Society
Society for Neuroscience
Vision Science Society
Service

Reviews for funding agencies

National Science Foundation (NSF, Mar 2007)

Reviews for conferences

Conference on Computer Vision and Pattern Recognition (CVPR)
European Conference on Computer Vision (ECCV)
International Conference on Computer Vision (ICCV)
International Conference for High Performance, Computing, Networking, Storage and Analysis (SC)
International Conference on Pattern Recognition (ICPR)
International e-Conference of Computer Science (IeCCS)
Neural Information Processing Systems (NIPS)

Reviews for journals

Animal Cognition (AC)
Biological Cybernetics (BC)
Computer Vision and Image Understanding (CVIU)
IET Computer Vision
Image and Vision Computing Journal (IMAVIS)
Iranian Journal of Electrical and Computer Engineering (IJECE)
International Journal of Computer Vision (IJCV)
IEEE Signal Processing Letters
IEEE Transactions on Image Processing (TIP)
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI)
International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI)
Journal of Artificial Intelligence Research (JAIR)
Journal of Experimental Psychology: Human Perception and Performance (JEP: HPP)
Journal of Vision
Neural Computation
Neurocomputing
Optical Engineering (OE)
Public Library of Science (PLOS)
Vision Research

 

Recent talks (since 2006)

May 2009   Vision Science Society (Naples, Florida)
Reading the mind’s eye: Decoding object information during mental imagery from fMRI patterns
>> slides

Apr 2009   Berkeley University, Redwood Center for Theoretical Neuroscience (Berkeley, CA)
Mechanisms of bottom-up and top-down processing in visual perception
>> Watch the presentation online
>> slides

Apr 2009    MIT, 2.151 Robotics (Boston ,MA)
Computational models of high-level vision

Apr 2009    MIT, 9.520 Statistical learning theory and applications (Boston ,MA)
Vision and visual neuroscience

Apr 2009   Mitsubishi Electric Lab MERL (Boston, MA)
A biologically-motivated approach to action recognition

Mar 2009   Janelia Farms research campus (Leesburg, VA)
Can computer science help neuroscience and vice-versa?

Mar 2009   Brown University, Department of Cognitive and Linguistics Sciences (Providence, RI)
Mechanisms of bottom-up and top-down processing in visual perception

Feb 2009   Boston University, CN 730 (Boston, MA)
Computational models of high-level vision

Dec 2008    NIPS Workshop on “Cortical microcircuits” (Vancouver, Canada)
Microcircuits for perception

Aug 2008   American Psychology Association (APA) Workshop on “How animals, humans, and computer models remember visual objects” (Boston, MA)
Computational models of object recognition in cortex

Sep 2008    Burroughs Wellcome Fund (Research Triangle Park)
Learning and recognition of temporal sequences in the visual cortex

Apr 2008    MIT, 9.520 Statistical learning theory and applications (Boston ,MA)
Vision and visual neuroscience

Mar 2008    Cosyne Workshop on “Dynamic faces” (Salt Lake, UT)
Processing of dynamic stimuli: A computational neuroscience perspective

Dec 2007    CIFAR NCAP Workshop on “Achieving perceptual invariance” (Vancouver, Canada)
Learning a dictionary of shape-components in visual cortex

Nov 2007    University of South California, Department of Psychology (Los Angeles, CA)
Learning a dictionary of shape-components in visual cortex

Oct 2007    CalTech, Department of Biology (Pasadena, CA)
Learning a dictionary of shape-components in visual cortex

Jul 2007     MIT, Small-talk seminar (Boston, MA)
Learning a dictionary of shape-components in visual cortex

Jun 2007    Workshop “A journey through computation” (Genoa, Italy)
Learning a dictionary of shape-components in visual cortex

May 2007   Vision Science Society (VSS), Sarasota (FL)
Rapid Serial Action Presentation: New paradigm for the study of movement recognition

May 2007   Mitsubishi Electric Research Laboratories (Boston, MA)
Learning a dictionary of shape-components in visual cortex

Apr 2007    MIT, 9.9520 Statistical learning theory and applications (Boston, MA)
Vision and visual neuroscience

Feb 2007    Cosyne Workshop on “Functional requirements of a visual theory” (Whistler, UT)
Functional requirements of a visual theory

Oct 2006    MIT, 9.912 Special topics in brain and cognitive sciences (Boston, MA)
Explaining rapid categorization

Jun 2006    McGovern retreat (Newport, RI)
A theory of object recognition in cortex: Predicting human performance

May 2006   MIT, 9.913 Pattern recognition for machine vision (Boston, MA)
Object recognition in cortex

Apr 2006    MIT, 9.520 Statistical learning theory and applications (Boston, MA)
Neuroscience and models of object recognition in the cortex

Feb 2006    MIT, Scene Understanding Symposium  (Boston, MA)
A feedforward architecture accounts for rapid categorization

Patents
Teaching
Massachusetts Institute of Technology Cambridge, MA.

MIT-IAP: Hierarchical learning: From understanding cortex to building a mathematical theory

since 2007

9.641 Neural networks

Teaching assistant for Prof. Sebastian Seung.

Fall 2005

9.63 Experimental psychology

Teaching assistant for Prof. Pawan Sinha.

Fall 2004

9.29 Computational neuroscience

Teaching assistant for Prof. Sebastian Seung.

Fall 2003