I am a computational immunologist and software engineer. I work as an
independent consultant helping clients
develop better vaccines and biologics using machine learning. I also develop
open source software, often as part of the OpenVax project.
From 2020-2022, I was a senior scientist at the Tisch Cancer Institute at
the Icahn School of Medicine at Mount Sinai. I worked on
therapeutic cancer vaccines with Nina Bhardwaj’s group
with the goal of helping these emerging therapies benefit more patients
through better antigen selection. We ultimately launched four Phase I clinical
trials at Mount Sinai to evaluate our platform for a fully personalized peptide
vaccine targeting tumor neoantigens.
From 2017-2020, I was a PhD student advised by Uri Laserson. My dissertation introduced
new methods for T cell epitope prediction, which are implemented in the
MHCflurry package. I also did some work
on antibody responses using phage immunoprecipitation
sequencing (PhIP-seq).
In 2018, Alex Rubinsteyn,
Julia Kodysh,
Tavi Nathanson and I launched the
OpenVax project to develop open source tools
for selecting cancer vaccines. This grew out of work with
Jeff Hammerbacher (2014-2017). The OpenVax tools
continue to be extended and have seen wide adoption by research groups and companies worldwide.
Prior to Mount Sinai, I worked at D.E. Shaw Research
(2009-2014) developing analysis software for molecular dynamics simulations.
Before this, I worked as a
software engineer, helped put together engineering teams
for several internet startups, and spent a summer interning at Google. I hold a
B.S. in Math & Computer Science from Brown University and
a PhD in Immunology from the Icahn School of Medicine at Mount Sinai.
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