I am a research scientist at Courant, New York University, and a PhD candidate at Université Paris-Est, under the supervision of Yann LeCun and Laurent Najman.
My research focuses on artificial vision in general: from the design and understanding of trainable vision systems, to their computation on efficient, low-power hardware.
+ Our new paper on efficient scene parsing: Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers.
+ We won the Optimization Challenge, held at the Transfer Learning and Optimization Workshop (in conjunction with NIPS 2011). Sixin Zhang presented some cool results on SGD, ASGD, weight initialization and weight tying for multi-layer auto-encoders.
+ Yann gave a cool 'discussant' talk at the Non-Parametric Bayesian (NPB) talk. It includes a concise summary of my work here (my stuff starts getting described at 10:00).
+ Yann and I gave an invited talk at the Big Learn Workshop (held in conjunction with NIPS 2011). The talk was about our latest work on neuFlow, convolutional networks, and some real-time scene parsing/understanding results. Here are my slides.
+ Scaling Up Machine Learning is ready for preorder. Our chapter, Large-Scale FPGA-Based Convolutional Networks is available here.