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Education

Research Experience

  • 2023 -
    Center for Theoretical Neuroscience
    Postdoc | Zuckerman Institute, Columbia University
    • Advisor: John Cunningham
    • Topics: Implicit regularization in deep learning, variational inference
  • 2019 - 2023
    Data to Actionable Knowledge (DtAK)
    Graduate Research Assistant | Harvard School of Engineering and Applied Sciences
    • Advisor: Finale Doshi-Velez
    • Topics: Bayesian neural networks, GPs, variational inference
  • 2019 - 2023
    Environmental Health
    Graduate Research Assistant | Harvard T.H. Chan School of Public Health
    • Advisor: Brent Coull
    • Topics: variable selection, approximate GPs
  • 2017 - 2018
    Prediction Analysis Lab
    Graduate Research Assistant | Duke University Department of Computer Science
    • Advisor: Cynthia Rudin
    • Topics: robust statistics, recidivism prediction, nonlinear dynamical systems
  • 2012 - 2013
    Soft Matter Theory
    Undergraduate Research Assistant | Tufts University Department of Physics
    • Advisor: Tim Atherton
    • Topics: Ising systems, critical phenomena in financial markets

Publications

Teaching Experience

  • 2019 - 2023
    Teaching Fellow
    Harvard University | Cambridge, MA
    • Data Science II | Biostatistics 261 (Spring 2021, 2022, 2023)
    • Reproducible Data Science | Biostatistics 270 (Winter 2022, 2023)
    • Applied Bayesian Analysis | Biostatistics 270 (Fall 2020, 2021)
    • Applied Regression Analysis | Biostatistics 210 (Fall 2019, Spring 2020)
  • 2017 - 2018
    Teaching Assistant
    Duke University | Durham, NC
    • Probabilistic Machine Learning | Statistical Science 561 (Spring 2018)
    • Data Analysis and Statistical Inference | Statistical Science 101 (Spring 2017)

Presentations

  • 2024
    • Invited talk at JSM session on Advances in Inference and Theory for Bayesian Neural Networks | Portland, OR
    • NSF AI Institute for Artificial and Natural Intelligence Visit Day | Columbia University
  • 2022
  • 2021
  • 2020
    • HughesLab group meeting | Virtual (PI Mike Hughes, Tufts University)
  • 2019
    • 12th International Conference on Bayesian Nonparametrics | Oxford, UK (poster)
  • 2018
    • Triangle Machine Learning Day | Durham, NC (poster)

Industry Experience

  • 2014 - 2016
    State Street Associates
    Assistant Vice President | Cambridge, MA
    • Lead analyst on the Liquid Private Equity Index, which tracks private equity with publicly traded securities.
    • Researched how market turbulence, systemic risk, illiquidity, and currency movements impact portfolio management
  • 2013 - 2014
    State Street Global Markets
    Senior Associate | Boston, MA
    • Completed three 4-month rotations through onboarding processes flows, currency hedging, and macro strategy (currency trading)
  • 2012
    State Street Associates
    Intern | Cambridge, MA
    • Worked on portfolio optimization by minimizing transaction costs