Bio

I am a Principal Data Scientist at Moderna Therapeutics and an alumni of Novartis, Insight Data Science, and MIT. My ScD thesis research was conducted in the Department of Biological Engineering at MIT. My thesis addresses two distinct topics that are unified by a mission for infectious disease. The first problem I have addressed is the ecological question of whether genome shuffling is quantitatively important for ecological niche switching. The second problem I am addressing is the data science problem of interpretable machine learning models for predicting protein phenotype from genotype. I believe in using open data, open science, and open source tools to ensure the long-term integrity of the scientific work that I conduct. To that end, I am committed to releasing source code and documentation for my scientific work, and have already done so on two manuscripts that are currently submitted and under consideration. I believe that great mentorship empowers individuals to give their best; thus, as others have been great mentors to me, I pay it forward through teaching avenues. My start with Python began in the Boston Python community in 2012; since then, I have given tutorials at PyCon, and guided 4 undergraduate students in our research group on computational research projects. Finally, I believe in building great teams, and not necessarily by being the leader. Great teams have commitment from their members, are focused on the most important goals, bring great joy to those on it and around them, and in turn deliver great results. I have brought this philosophy to the inaugural 2009 UBC iGEM team, where we won a Gold medal standing in our first attendance at the iGEM Jamboree, and to the Tang Hall Residents' Association at MIT, where we introduced transparency and accountability measures for officer performance, and increased the publicity and frequency of socials.