About me

Hello! I'm currently working as a Data Scientist at Stanford RegLab, with a team of interdisciplinary researchers trying to improve governance through responsible and fair data science. For example, we work with the Environmental Protection Agency on projects using computer vision + remote sensing to detect violations of environmental policy.

Previously, I was studying public policy and data analytics at Carnegie Mellon University. Alongside courses in machine learning and optimization, I learnt about AI ethics, design thinking, transportation systems, and more.

I also spent close to 5 years working at the Poverty Action Lab (J-PAL) on various projects with Indian state government departments. My team used administrative data to provide quick insights on programs, identify data quality improvements, and scope longer-term impact evaluations/experiments.

I hold a Bachelor’s degree in Economics from the University of Cambridge.

What I've worked on

  • Machine Learning

    Classification and regression problems using structured data

  • Data cleaning and analysis

    With various messy survey and admin datasets across sectors

  • Causal inference

    Experiment design and analysis, quasi-experimental methods

  • Optimization

    Linear and integer programming applied to decisions like facility location, resource allocation

  • Project management

    Team and budget management, working with technical and non-technical stakeholders

  • Survey design and execution

    Questionnaire development, monitoring survey data collection

Check out the portfolio section of the site to see some examples of my work!


Click here to view my full, detailed resume


  1. Carnegie Mellon University

    2021 — 2023 (expected)

    Master of Science in Public Policy and Data Analytics

  2. University of Cambridge

    2013 — 2016

    Bachelor of Arts in Economics


  1. Research Manager - Data

    2019 — 2021

    At the Poverty Action Lab (J-PAL), I helped set up and grow a unit that worked closely with state governments on their administrative data. I also helped build internal processes and policies for handling data.

  2. Research Associate - Data

    2017 — 2019

    At J-PAL, I analysed several administrative datasets across sectors, working with government partners to communicate and iterate over findings. I also helped conduct trainings for staff on data quality and visualization.

Technical skills

  • Programming: Python, SQL, R, STATA
  • Frameworks: Scikit-Learn, Spark, Gurobi, Dash
  • ML: supervised and unsupervised learning


Click on the project to be redirected to a page with more info (e.g. GitHub repo with README, slides).