Vision, Learning and Graphics group,
Dept. of Computer Science,
Courant Institute of Mathematical Sciences,
New York University
I am currently on leave from NYU, working as a Research Scientist at Facebook AI Research.
However, I am looking to recruit PhD students this year (i.e. to start in Fall 2016).
Room 1226, 715 Broadway,
New York, NY 10003, USA.
Directions to lab
My research is in the areas of Machine Learning and Computer Vision. I am particularly interested in applying Deep Learning methods to object recognition. I also work on low-level vision problems, with applications to computational photography and astronomy.
Deep Learning for Computer Vision
NIPS 2013 Tutorial [Slides]
Online Recognition Demo
See our deep convolutional network demo here. This network achieves 16.5% top-5 error on the Imagenet 2012 classification challenge, around 2% better than the network of Krizhevsky et al. (NIPS 2012).
Pre-prints of recent research can be found on arXiv: Link
Visualizing and Understanding Convolutional Networks
Matt Zeiler and Rob Fergus,
ECCV 2014, PDF
Reconnaissance of the HR 8799 Exosolar System I: Near IR Spectroscopy
Indoor Segmentation and Support Inference from RGBD Images
Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
Learning Invariance through Imitation
Blind Deconvolution using a Normalized Sparsity Measure
Dark Flash Photography
80 million tiny images: a large dataset for non-parametric object and scene recognition