Vision, Learning and Graphics group,
Dept. of Computer Science,
Courant Institute of Mathematical Sciences,
New York University
Director of Graduate Studies for Master of Science in Data Science
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.
International Conference on Learning Representations 2013
I am one of the Program Chairs for a new conference on feature learning and representation learning. Check out the website.
Deep Learning Methods for Vision
CVPR 2012 Tutorial
Speakers: Rob Fergus (NYU), Honglak Lee (Michigan), Marc'Aurelio Ranzato (Google) Ruslan Salakhutdinov (Toronto), Graham Taylor (Guelph), Kai Yu (Baidu)
Reconnaissance of the HR 8799 Exosolar System I: Near IR Spectroscopy,
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks,
Indoor Segmentation and Support Inference from RGBD Images
Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
Learning Invarance 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