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  • B.S. in Physics, MIT, 2014
  • Ph.D in Astronomy & Statistics, UC Santa Cruz, 2019

Work experience

  • 2019 - : Data and Applied Scientist — Microsoft

  • 2014-2019: NSF Graduate Research FellowUCSC
    • 2019: Adapted one-by-one convolutions to extend networks pretrained on 3-band (RGB) images to arbitrarily many bands
    • 2018: Developed conditional Generative Adversarial Networks (cGANs) to create synthetic galaxy images to augment training of other neural networks (tensorflow)
    • 2017: Built image classifier using Convolutional Neural Networks and Random Forests to identify dwarf galaxies (Python, keras)
    • 2016: Published Bayesian statistic analysis of supernova simulations
    • 2015: Extended distributed software for simulating supernovae (C/C++) which scales well to at least 1000 cores and has run for over 250,000 CPU hours
  • Summer 2018: Data Science InternMicrosoft
    • Building unsupervised deep learning models to identify the key differences between natural language corpora (tensorflow)
    • Designing interpretable, online models to predict future search volume (scikit-learn)
  • Summer 2017: Data Science InternLendUp (consumer lending startup)
    • Predicted risk of credit card applicants using statistical modeling (Python, SQL)
    • Engineered new features to extract insights from previously unused data
    • Performed exploratory data analysis to support new product development
    • Identified and created ETL solutions for the unmet needs of other teams
  • 2013 - 2014: Undergraduate ResearcherMIT Kavli Institute for Astrophysics
  • Summer 2013: Visiting Research Fellow — Universität Heidelberg
    • Extended and optimized data pipeline to detect trace atmospheric gases


Python, tensorflow, keras, pytorch, C++/C, SQL, R, scikit-learn

Selected Awards

2016-2019: NSF Graduate Research Fellow

  • $138,000 award supporting my PhD research; 2,000 fellows selected from 17,000 applicants

2015-2018: Osterbrock Prize Leadership Fellow (UC Santa Cruz)

  • $5,000 award with continued mentoring to develop technical leadership skills