Data Scientist & Researcher
I work as a data scientist at AE Studio.
From 2019 to 2024, I worked at Jellyfish, where I ran a few hackathons, mentored some great interns, and built features that modeled how engineers interact and complete projects.
I studied physics at MIT (2009-2013) and Harvard (2014-2019). In undergrad, I explored multiple supersymmetry breaking as a model of dark matter, and as a PhD student, I explored statistical physics and combinatorics of biomolecular interactions as a grad student.
In 2017 and 2018, I taught in MIT's MITES program, which inspired me to publish some ideas on enhancing physics education ("The Missing Curriculum in Physics Problem-Solving Education"). Below are some research papers and presentations.
I post essays at Perturbations.
(2024) Large W limit of the knapsack problem.
Physical Review E,
109(4),
044151
(One Page
Summary)/PhysRevE.109.044151
(2022) Derangement model of ligand-receptor binding.
Computational and
Mathematical
Biophysics, 10(1), pp.123-166
(One Page
Summary)/[arxiv:2201.09471]
(2019) Self-assembly of a dimer system.
Physical Review E, 99(4),
042133.
(One Page
Summary)/[arxiv:1909.00455]
(2018) Permutation glass.
Physical Review E, 97(1), 012139.
(One Page
Summary)/[arxiv:1801.03231]
(2018) Missing Curriculum in Physics Problem Solving Education.
Science &
Education27.3: 299-319.
[Science & Education, 27(3),
pp.299-319.]
(2017) Statistical physics of the symmetric group.
Physical Review
E, 95(4),
042126.
(One
Page
Summary)/[PhysRevE.95.042126]
(2013) Multiply Supersymmetry Breaking as a Model of Dark Matter.
MIT
Physics
[Thesis PDF]