am a Ph.D student in computer science at the Courant Institute of
Mathematical Sciences. Before that I worked at the Center for Health
Informatics and Bioinformatics at the NYU Medical Center, and finished
my M.S. in math at NYU. Earlier still, I did my undergrad in
pure math at the University of Texas at Austin.
My research interests are in statistical machine learning and its many
applications, especially bioinformatics, computer vision and music information
Music is my other passion, and I also DJ/produce electronic music and
run a radio project for the community arts organization Arts in
Bushwick to promote emerging artists and musicians.
- "Fast Training of Convolutional Networks through FFTs." Michael Mathieu, Mikael Henaff and Yann LeCun (submitted)
Learning of Local Causal Pathways." Alexander Statnikov, Mikael Henaff,
Nikita Lytkin, Efstratios Efstathiadis, Eric Peskin, Constantin F.
Signatures of Psoriasis: Feasibility and Methodology Comparison".
Alexander Statnikov, Alexander Alekseyenko, Zhiguo Li, Mikael Henaff,
Martin Blaser and Constantin Aliferis. Nature Scientific Reports (2013).
Comprehensive Evaluation of Multicategory Classification Methods for
Microbiomic Data." Alexander Statnikov, Mikael Henaff, Varun Narendra,
Kranti Konganti,Zhiguo Li, Liying Yang, Zhiheng Pei, Martin Blaser, Constantin Aliferis and Alexander Alekseyenko. Microbiome (2013)
- "New Methods for
Separating Causes from Effects in Genomics Data." Alexander Statnikov,
Mikael Henaff, Nikita Lytkin and Constantin Aliferis. BMC Genomics
- "Unsupervised Learning of Sparse Features for Scalable Audio
Classification." Mikael Henaff, Kevin Jarrett, Koray Kavukcuoglu and
Yann LeCun. Proceedings of the International Society for Music
Information Retrieval (ISMIR 2011)
- "Efficient Sparse Coding for Music Information Retrieval." Mikael Henaff. Master's Thesis (2011)