My lab is recruiting masters and PhD students who are interested in working on new machine learning algorithms based on convex and discrete optimization – if you are interested in joining my lab please email me your CV and a cover letter.
- 2018-present: Assistant Professor, Northern Arizona University, School of Informatics, Computing, and Cyber Systems.
- 2014-2018: Postdoc, McGill University, Human Genetics Department, with Guillaume Bourque.
- 2013: Postdoc, Tokyo Institute of Technology, Computer Science Department, with Masashi Sugiyama.
- 2009-2012: PhD student, Ecole Normale Superieure de Cachan, Computer Science Department, with Francis Bach and Jean-Philippe Vert.
- 2008-2009: Masters student, Université Paris 6, Statistics Department, with Mathieu Gautier and Jean-Louis Foulley.
- 2006-2008: research assistant at Sangamo BioSciences.
- 2002-2006: undergraduate, UC Berkeley, Double major in Molecular & Cell Biology and Statistics, with Terry Speed.
- Full CV
Research interests: fast and accurate algorithms for convex optimization (clustering, regression, ranking, classification) and discrete optimization (changepoint detection, dynamic programming). The main application domain for the algorithms I develop are in genomic data analysis (DNA copy number, ChIP-seq, etc); other applications include neuroscience, audio, internet, sensors, recommendation and ranking systems.
I think reproducible research is important, so in addition to every paper I write, I also provide
- A reference implementation of the algorithm(s) described in the paper, typically as an R package.
- Source code for doing the analyses and creating the figures, typically in a GitHub repo.
If you want to send me encrypted/signed messages, you can use my GPG key (fingerprint 1D46 6295 2738 32E6 F70B 9F64 45B0 8611 CDB1 FA96).
My ORCID is 0000-0002-3146-0865.
|Feb 27, 2019||Our paper about Fast nonconvex deconvolution of calcium imaging data has been published in Biostatistics.|
|Oct 30, 2018||Our paper about Meta-mining of copy number profiles of high-risk neuroblastoma tumors has been published in Scientific Data.|
|Sep 16, 2018||Our paper about a supervised machine learning method for predicting pathogenicity of genetic variants has been accepted in the American Journal of Human Genetics.|
|Aug 24, 2018||Our paper about interactive extensions to the grammar of graphics has been accepted in the Journal of Computational and Graphical Statistics.|
|Mar 8, 2018||Our paper about Novel Markers for Poor Survival in High-risk Neuroblastoma Patients has been published in the Journal of the National Cancer Institute.|