Karteek Alahari

Inria Grenoble - Rhône-Alpes - Thoth project-team
655 avenue de l'Europe, Montbonnot
38334 Saint Ismier Cedex
France (sending mail)

Email: karteek (dot) alahari @ inria (dot) fr
Fax: +33 4 76 61 54 54
Karteek Alahari



I am a tenured researcher (chargé de recherche Inria) in the Thoth research team (formerly known as LEAR), based at the Inria Grenoble - Rhône-Alpes center.

I was previously a postdoctoral fellow in the Inria WILLOW team at the Department of Computer Science, École Normale Supérieure (ENS), where I worked with Ivan Laptev, Jean Ponce, and Josef Sivic. I completed my Ph.D. in July 2010, under the supervision of Philip Torr. I am also an associate member of the Visual Geometry Group, University of Oxford and the WILLOW team at ENS.

My current research focuses on addressing the visual understanding problem in the context of large-scale datasets. In particular, I work on learning robust and effective visual representations, when only partially-supervised data is available. This includes frameworks such as incremental learning, weakly-supervised learning, adversarial training, etc.




CV PUBLICATIONS SOFTWARE & DATASETS RESEARCH GROUP TEACHING
updated: Apr 2022 complete list, Google scholar, DBLP





NEWS (A complete list is here)
  • Our work on image-goal navigation, learning goal-conditioned policies and bird's-eye-view segmentation are accepted at IROS 2022 and CoRL 2022.
  • I was a speaker at the Open Data Science Conference (ODSC Europe) in June.
  • I was a program co-chair for BMVC 2021: 22-25 November.
  • Our papers accepted at NeurIPS 2021, WACV 2022, and CVPR 2022 are now available.
  • I was an area chair / senior program committee member for ECCV 2022, ICCV 2021, CVPR 2021, ECCV 2020, CVPR 2020, AAAI 2020, IJCAI 2020.




    RESEARCH GROUP

    Postdoc: Research engineer: PhD students: Graduated: Masters: Former postdocs:




    TEACHING

    2021-'22: Graphical Models: Inference and Learning (MVA course at CentraleSupélec, Paris)
    2021-'22: Understanding Big Visual Data (at ENSIMAG, in French)
    2021-'22: Introduction to Computer Vision (at ENS Paris)
    2021-'22: Machine Learning for Multimodal Data (at ENSIMAG)
    2020-'21: Graphical Models: Inference and Learning (MVA course at CentraleSupélec, Paris)
    2020-'21: Understanding Big Visual Data (at ENSIMAG, in French)
    2020-'21: Introduction to Computer Vision (at ENS Paris)
    2020-'21: Machine Learning for Computer Vision and Audio Processing (at ENSIMAG)
    2019-'20: Graphical Models: Inference and Learning (MVA course at CentraleSupélec, Paris)
    2019-'20: Category Learning and Object Recognition (at ENSIMAG)
    2019-'20: Understanding Big Visual Data (at ENSIMAG, in French)
    2019-'20: Introduction to Computer Vision (at ENS Paris)
    2018-'19: Graphical Models: Inference and Learning (MVA course at CentraleSupélec, Paris)
    2018-'19: Introduction to Computer Vision (at ENS Paris)
    2018-'19: Understanding Big Visual Data (at ENSIMAG, in French)
    2018-'19: Machine Learning and Object Recognition (at ENSIMAG)
    2017-'18: Discrete Inference and Learning (MVA course at CentraleSupélec, Paris)
    2017-'18: Introduction to Computer Vision (at ENS Paris)
    2017-'18: Understanding Big Visual Data (at ENSIMAG, in French)
    2016-'17: Introduction to Discrete Optimization (at École Centrale Paris)
    2016-'17: Understanding Big Visual Data (at ENSIMAG, in French)
    2015-'16: Introduction to Discrete Optimization (at École Centrale Paris)
    2014-'15: Multimedia databases (at ENSIMAG, in French)
    2013-'14: Multimedia databases (at ENSIMAG)





    PERSONAL






    *Photo courtesy: V. Peregrin.