Since September 2014, I am an Assistant Professor in the College of Information and Computer Sciences at the University of Massachusetts, Amherst and the co-director of the Computer Vision Lab. I am affilated with the Center of Data Science and AWS AI. Prior to this I spent three years as a Research Assistant Professor at TTI Chicago, a philanthropically endowed academic computer science institute in the University of Chicago campus. I obtained my Ph.D. under the supervision of Jitendra Malik from the University of California at Berkeley in 2011, and a B.Tech. in Computer Science and Engineering from IIT Kanpur in 2006. In the past I have enjoyed working at Google, INRIA LEAR group, Microsoft Research India, the CLSP center at Johns Hopkins University, and Oxford University. My research is funded by the National Science Foundation, including a CAREER, as well as faculty grants from Facebook, NVIDIA, and Adobe.
My research focusses on computer vision with a particular emphasis on algorithms for high-level recognition. My goal is enable cheap and robust sensing of the visual world using cameras powered by computer vision. For an overview of my research take a look at my recent publications and projects. I am also on Google scholar.
A better computer science department rankings for PhD students: http://csrankings.org.
|2/20||Organizing Fine-grained Visual Categorization (FGVC7) workshop at CVPR 2020. Call for papers posted.|
How has nocturnal bird migration shifted in the last 20+
years? See our latest paper at
roost detection project will appear at AAAI 2020.
Matheus for winning the best poster and an
honorable mention at the New England Computer Vision
Workshop held at Brown
University this year.
I will serve as an Area Chair for
CVPR 2020 and ECCV 2020||10/19|| At ICCV I'll be (1) giving invited talks at the
Vision Modeling workshop, the
Computer Vision for
Wildlife Conservation workshop, and a tutorial on
image representations; and (2) presenting two papers.
|9/19||Teaching Computer Vision @ UMass|
NSF grant awarded on 3D shape understanding with Rui Wang
|8/19||Recent preprints and upcoming
papers (see publications):
+ MistNet appears in Methods in Ecology and Evolution (press release)
+ Two papers to appear at ICCV 19 and one at 3DV 19
+ Two papers to appear at CVPR 19 and one at AAAI 19, UBICOMP 19, KDD 19
+ Journal accepted on IEEE Trans. on Info. Theory
+ ArXiv highlights: Task2Vec, PrGAN++
|2/19||Invited talk at ICERM @ Brown University. Talk slides.|
workshop at CVPR 19.
+ Several competetions are live. Participate to win prizes!
+ Call for papers posted.
|1/19||I'll serve as an area chair for CVPR 19 and on the SPC for IJCAI 19.|
|1/19||Teaching Intro to Computer Vision (370) @ UMass|
|10/18||NSF grant awarded for machine learning for Astronomy.|
|8/18||A recent talk at Caltech summarizing our work on 3D shape generation.|
|7/18||Two papers and a workshop paper accepted to ECCV 18.||6/18||SPLATNet won the best paper honorable mention at CVPR 18. Popular press: UMass, NVIDIA, Medium|
|6/18||NSF CAREER grant awarded. University press release.|
|5/18|| Upcoming papers and workshops:
+ VisemeNet to appear @ SIGGRAPH 18
+ Two papers: SPLATNet, CSGNet to appear @ CVPR 18
+ Fine-Grained Visual Categorization (FGVC5) workshop @ CVPR 18
|4/18||Invited talk at the annual data science resesarch symposium.|
|1/18||Teaching Intro to Computer Vision (370) @ UMass|
|12/17||I will serve as an area chair for CVPR 2018.|
|10/17||Invited talk at the Manifold Learning Workshop @ ICCV 17.|
|7/17||Dark ecology project funded by NSF. Link to the press release.|
|7/17||Upcoming papers and recent preprints:
+ 2 papers at 3DV, 3 papers at BMVC 17, 1 at ICCV 17 (see publications) + Bilinear CNNs PAMI preprint, arXiv v6, Jun 2017
+ 3D Shape Segmentation with Projective Convolutional Networks, CVPR 17 (oral presentation)
+ 3D Shape Reconstruction from Sketches via Multi-view Convolutional Networks, arXiv, July 17
|4/17||Department colloquium speaker at RIT and UoR.|
|9/16||Teaching Computer Vision @ UMass|
|6/16||Received NSF grant for language-based understanding of textures, and a gift from Facebook.|
- 670: Computer Vision [Fa19, Fa18, Fa17, Fa16, Fa14]
- 370: Introduction to Computer Vision [Sp19, Sp18, Sp17, Sp16]
- 689: Machine Learning [Sp15]
- Higher-order Representations in Computer Vision, ICCV 2019
- Additive Classifiers for Computer Vision, ECCV 2012
- Topics in Computational Visual Recognition, ICVGIP 2012
- Fine-Grained Visual Categorization(FGVC7), CVPR 2020
- Fine-Grained Visual Categorization (FGVC6), CVPR 2019
- Fine-Grained Visual Categorization (FGVC5), CVPR 2018
- Fine-Grained Visual Categorization (FGVC4), CVPR 2017
- Fine-Grained Visual Categorization (FGVC3), CVPR 2015
- New England Computer Vision, Amherst, MA 2015
- Computer Vision and Human Computation, CVPR 2014
Past student advisees and collaborators:
I occasionally draw and paint.