The members of our group are working on projects that involve developing new statistical models, optimization algorithms, interactive systems, and software for machine learning.

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Convex optimization algorithms for clustering, ICML’11 Constrained changepoint detection algorithms, ICML’15 Supervised learning for peak detection in epigenomic data, Bioinformatics (2017)


The lab is recruiting undergraduate, masters, and PhD students who are interested in working on convex and discrete optimization algorithms, data visualization techniques, and interactive systems for machine learning – if you are interested in joining please email lab director with your CV and a cover letter.


Paid research internships are available for students interested in developing new algorithms/software for supervised changepoint detection in large data sequences.

Coding Internships. To support our research projects, our lab develops free/open-source software packages for machine learning. To teach students how to code free/open-source software for machine learning, we participate as mentors in Google Summer of Code (for college students) and Google Code-In (for high school students during winter break).