I am biologist and computer scientist currently working at Moderna Therapeutics. My research efforts focus on applying machine learning and statistical techniques to improve our mRNA medicines. In particular, I am most excited about using unsupervised and generative deep learning methods to understand the complex relationships between sequence and function in mRNA and protein molecules.
More broadly, I am interested in computation (neural and otherwise), mathematical modelling and data visualization, as well as applying cutting edge analytic methods to data of all sorts and domains. This page lists my published scientific papers and side projects.
I believe that open source software is a crucial part of open science. In a previous life, I wrote d_code, an analysis package for in vivo Ca Imaging and Electrophysiology analysis. I am also a contributor to a number of open source software projects, to varying degrees:
- PyTorch - A deep learning framework that puts Python first
- Thunder - Large-scale image and time series analysis in Apache Spark
- Bolt - Distributed multi-dimensional arrays in Python using Apache Spark
- Folium - Python wrapper for the leaflet.js map library
Previously, I was a postdoctoral fellow in the Department of Neurobiology, working in Sandeep Datta's lab, and before that I earned my doctorate with Bernardo Sabatini. During my Ph.D., I studied neuromodulation and synaptic calcium signaling in the dendrites and dendritic spines of hippocampal neurons. My projects during my postdoc used in vivo electrophysiological, imaging, and optogenetic approaches to understanding the circuit and cellular properties of the mammalian olfactory system. A list of my neurobiology publications follows.