I am a post-doctoral fellow in computational biology. My primary training is in machine learning and statistics, but I have been working in bioinformatics for almost nine years. For my PhD, I developed algorithms for classification and characterization of cellular phenotypes from cell image data. In my current position at MSKCC, I'm working on generative models of in vivo chromatin structure using HiC data. I enjoy working on projects that use machine learning in novel ways to yield biological insights.
Specialties: machine learning, statistics, Python, R, Linux, image analysis
? 5 years of experience in biological image modeling including cluster-based distributed image analysis pipelines (Cell Profiler), image analysis, data mining and visualization.
? 9+ years of experience in bioinformatics, machine learning, Linux-based high-performance computing environments (Python (NumPy, SciPy, Matplotlib), R, CUDA, C++, bash scripting, multi-core and distributed parallel computing (openMP, Open MPI)).
? 2 years of experience in modeling gene regulation, epigenomic regulation, chromatin organization.
? Speaks English (native), French (near fluency)