Jitendra Malik

Arthur J. Chick Professor of EECS
University of California at Berkeley
CA 94720-1776
Asst: Angie Abbatecola, angie@eecs.berkeley.edu
Email: malik@berkeley.edu
Prospective graduate students-you do not need to contact me. Follow this link instead.

Office: Berkeley Way West

Brief Bio

Curriculum Vitae

Publications List

Academic Family Tree as of 2010

Teaching Spring 2015: CS 280 Computer Vision

Research Projects before 2015

Publications before 2010

Selected Talks

Current Ph.D. Students

 * Anastasios Angelopoulos
 * Toru Lin
 * Vongani Maluleke
 * Karttikeya Mangalam
 * Ilija Radosavovic
 * Jathushan Rajasegaran
 * Neerja Thakkar
 * Haozhi Qi

Current Postdoctoral Fellows

 * Shiry Ginosar
 * Antonio Loquercio
 * Georgios Pavlakos

Former Ph.D. Students

 * Paul Kube On Image Texture, 1988 , UC San Diego
 * Pietro Perona Finding Texture and Brightness Boundaries in Images, 1990, Caltech
 * Niklas Nordstrom Variational Edge Detection, 1990
 * Ziv Gigus Object Recognition from Line Drawings, 1991
 * Clark Olson Fast Object recognition by Selectively Examining Hypotheses, 1994, U W Bothell
 * David G. Jones Computational Models of Binocular Vision, 1991 , McMaster
 * Joseph Weber The Measurement and Use of Visual Motion, 1994 , TiVo
 * Ruth Rosenholtz Local Shape from Texture, 1994 , MIT
 * Paul Debevec Modeling and Rendering Architecture from Photographs, 1996 , USC ICT
 * Christoph Bregler Computational Models of Human Motion, 1998 , Google
 * Jianbo Shi Perceptual Organization and Image Segmentation, 1998 , University of Pennsylvania
 * Chad Carson Region-Based Image Querying and Classification, 1998 , Yahoo!
 * Yizhou Yu Modeling and Editing Real Scenes with Image-Based Techniques, 2000 , Univ. Hong Kong
 * Thomas K. Leung Visual Texture Analysis, 2000 , Google
 * Serge J. Belongie Image Segmentation and Shape Matching for Object Recognition, 2000 , Cornell Tech
 * David Martin An empirical approach to Grouping and Segmentation , 2002 , Google
 * Alyosha Efros Data-driven Approaches for Texture and Motion, 2003 , UC Berkeley
 * Laura Walker Parts, Objects and Scenes: Computational Models and Psychophysics, 2003 , Apple
 * Gregory Mori Detecting and Localizing Human Figures, 2004 , Simon Fraser University
 * Andras Ferencz Finding Good Features for Object Recognition, 2005 , Mobileye Vision Technologies
 * Charless Fowlkes Measuring the Ecological Validity of Grouping and Figure-Ground Cues, 2005 , UC Irvine
 * Alexander Berg Shape Matching and Object Recognition, 2005 , UNC Chapel Hill
 * Xiaofeng Ren Probabilistic Models for Mid-Level Vision, 2006 , Amazon, Seattle
 * Hao Zhang Adapting Learning techniques for Visual Recognition, 2007,Two Sigma
 * Andrea Frome Learning Distance Functions for Exemplar-Based Object Recognition, 2007,Clarifai
 * Michael Maire Contour Detection and Image Segmentation, 2009,Chicago
 * Ashley Eden Finding Lost Children, 2010,Google
 * Lubomir Bourdev Poselets and Their Applications in High-Level Computer Vision, 2011, WaveOne
 * Chetan Nandakumar Invariance in Human Visual Perception, 2011
 * Subhransu Maji Algorithms and Representations for Visual Recognition, 2011, University of Massachussets, Amherst
 * Chunhui Gu Recognition Using Regions, 2012, Startup
 * Jon Barron Shapes, Paint, and Light, 2013, Google
 * Bharath Hariharan Beyond Bounding Boxes: Precise Localization of Objects in Images, 2015, Cornell University
 * Georgia Gkioxari Contextual Visual Recognition from Images and Videos, 2016, Facebook AI Research
 * Abhishek Kar Learning to Reconstruct 3D Objects, 2017, Google
 * Shubham Tulsiani Learning Single-view 3D Reconstruction of Objects and Scenes, 2018, Facebook AI Research
 * Saurabh Gupta Representations for Visually Guided Actions, 2018, FAIR / University of Illinois Urbana-Champaign
 * Pulkit Agrawal Computational Sensorimotor Learning, 2018, Massachusetts Institute of Technology
 * Panna Felsen Learning to Predict Human Behavior from Video, 2019, Startup
 * Weicheng Kuo Expert-Level Detection of Acute Intracranial Hemorrhage on Head Computed Tomography using Deep Learning, 2019, Google Brain
 * Ke Li Advances in Machine Learning: Nearest Neighbor Search, Learning to Optimize and Generative Modeling, 2019, Simon Fraser University
 * Zhe Cao Perceiving 3D Humans and Objects in Motion, 2021, Google
 * Jasmine Collins Bridging the Gap between Humans and Machines in 3D Object Perception, 2023, Startup
 * Alexander (Sasha) Sax Pretrained Representations for Embodied AI, 2023, FAIR, Meta, Inc.
 * Shubham Goel High-Fidelity 3D Mesh Reconstruction of Humans and Objects, 2023, Avataar
 * Ashish Kumar Rapid Adaptation for Robot Control, 2023, Tesla

Former Postdoctoral fellows, excluding my former PhD students

 * Roberto Manduchi
 * Dieter Koller
 * Quang-Tuan Luong
 * David Beymer
 * Camillo J. Taylor
 * Phil McLauchlan
 * Jana Kosecka
 * Jan Puzicha
 * Yair Weiss
 * ZuWhan Kim
 * Stella Yu
 * Erik Learned-Miller
 * Eran Borenstein
 * Bjorn Ommer
 * Pablo Arbelaez
 * Thomas Brox
 * Cees Snoek
 * Ross Girshick
 * Joao Carreira
 * Katerina Fragkiadaki
 * Christian Haene
 * David Fouhey
 * Angjoo Kanazawa
 * Amir Roshan Zamir
 * Andrea Bajcsy

Jitendra Malik (malik@eecs.berkeley.edu)