I am a Principal Investigator and Assistant Attending Computational Oncologist in the Department of Epidemiology and Biostatistics at Memorial Sloan Kettering Cancer Center. My work is focused on statistical machine learning methods and applications to cancer. If you are a PhD student or postdoc interested in working with me, please email me.
Before joining MSK, I was a postdoc at Columbia University and Columbia University Medical Center in New York. I worked with David Blei and Chris Wiggins at the Data Science Institute, and Raul Rabadan in the Program for Mathematical Genomics in Systems Biology.
I did my PhD in Computer Science at UT Austin working with James Scott. My PhD focused on machine learning methods with health and wellness applications, particularly those involving graphical models, Bayesian statistics, and scalable inference algorithms. I worked on projects ranging from obesity and nutrition modeling to wearable fitness devices and large-scale multiple hypothesis testing for fMRI studies.
In a previous life, I was a software engineering researcher working with Eli Tilevich at Virginia Tech, where I got my BS and MS in Computer Science. My Master's thesis focused on inference techniques that learn transformation rules to automatically upgrade legacy applications to use the latest version of a given API. I've also co-founded a couple of startups and was a quant at a hedge fund.