About Me

I am a fourth year undergraduate in Computer Science and Statistics at Harvard University where I am advised by Yaron Singer and David Parkes.

My research is at the intersection of machine learning and the social sciences. I am attracted by the dynamic nature of social data and the algorithmic and statistical challenges it entails. The problems I engage with are of importance as we are increasingly using ML to improve decision-making in domains like business, politics and legal systems.


Robust Classification of Financial Risk
with Daniel Giebisch, Suproteem Sarkar and Yaron Singer
NIPS 2018 Workshop on AI in Financial Services
Oral Presentation

Working Papers

Label Propagation Networks
with Nir Rosenfeld and Amir Globerson

Predicting Choice with Set-Dependent Aggregation
with Nir Rosenfeld and Yaron Singer

Work Experience

I have worked for a $9B e-commerce with 300M users as a machine learning engineer, launched a Tokyo branch of a Harvard-MIT data consulting firm, and helped build a tool every Android developer uses.



Programming: Python, R, Matlab, SQL, C++, Go, Ruby
Machine Learning: TensorFlow/Keras, PyTorch, Pyro, Edward
DB & Infrastructure: MongoDB, AWS, Hadoop, Docker
Open Source Contributions: Homebrew, FFaker (Rails library)
Side Projects: Virtual Reality Pet, a Google Cardboard app with 12,000+ downloads.



Honorable Mention, Computing Research Association Outstanding Undergraduate Researcher Award, 2019

Recipient, Funai Overseas Scholarship, 2019

Selected Coursework

Undergraduate Courses
Linear Algebra, Algorithms and Data Structures, Theory of Computation, Real Analysis

Graduate Courses
Probability, Inference, Optimization, Machine Learning, Economics and Computation, Causal Inference, Econometrics Theory (two courses), Nonasymptotic Statsitics, High Dimensional Probability