CV for Michael C. Hughes

PDF | source | Last updated: June 12 2017

Education


  • Brown University

    May 2016

    Ph.D., Computer Science

  • Brown University

    May 2012

    M.S. Computer Science

    GPA: 4.0

  • Olin College of Engineering

    May 2010

    B.S. Electrical & Computer Engineering

    GPA: 3.93

Research Experience


  • Postdoctoral fellow: Machine learning for clinical interpretability

    Fall 2016 - present

    Adviser: Prof. Finale Doshi-Velez (Harvard)

    • Collaboration with MGH to improve prediction of drugs for mental health patients
    • Collaboration with MIT to better suggest interventions in the ICU
    • Supported by gift from Oracle
  • Estimating carbon biomass from LiDAR waveforms

    Summer 2016

    Adviser: Prof. Erik Sudderth & Prof. Jim Kellner (Ecology & Evolutionary Biology)

    • Predicted forest biomass from LiDAR waveforms to better understand land use and climate change
    • Developed Bayesian nonparametric regression to jointly model waveforms and biomass values
    • Intended for use in upcoming NASA mission GEDI
  • Ph.D. Thesis: Scalable inference for Bayesian nonparametric clustering

    Spring 2016

    Adviser: Prof. Erik Sudderth

    • Developed variational inference algorithm that adapts to data by adding or removing clusters during training.
    • Optimizes sophisticated objective function based on marginal likelihood for Ockham's razor model selection.
    • Applicable to mixture models, topic models, and hidden Markov models.
    • Implemented algorithms in open-source Python package BNPy.
  • Master's Project: Sequential Models for Video and Motion Capture

    Spring 2012

    Adviser: Prof. Erik Sudderth

    • Developed methods to discover common actions from many videos of humans performing common activities.
    • Improved existing MCMC inference algorithms with data-driven Metropolis-Hastings proposals.

Honors and Awards


  • Spring 2011

    NSF Graduate Research Fellowship Award

    • Three year funding award. Covers tuition and provides research stipend.
  • Spring 2011

    NDSEG Graduate Research Fellowship Award

    • Three year funding award. Declined to accept NSF fellowship.

Publications


Industry Experience


  • Google , Mountain View

    Summer 2013

    Software Engineering Intern

    • Improved walking/biking/running classifier using smartphone accelerometer data.
    • Led collection of dataset from dozens of individuals for classifier evaluation.

Non-profit Experience


  • Harvard Humanitarian Initiative , Cambridge, MA

    2014

    Signal Program Fellow

    • Developed prototype detector for common housing structures in sub-Saharan Africa from satellite images.
    • Intended for humanitarian oversight of conflict areas where burning structures is common attack pattern.
    • Featured in TEDx talk: http://youtu.be/u7l9rBwOnwU

Teaching Experience


Professional Service


  • 2016

    Workshop Organizer

    • Practical Bayesian Nonparametrics workshop at NIPS '16
    • Full day workshop with invited speakers, contributed talks, two panel discussions, and lively poster session
    • Led decisions on >25 submitted papers based on peer review
  • 2016

    Invited Panelist

  • Program Committee / Reviewer

    • AAAI 2018
    • NIPS 2017
    • ICML 2017
    • AAAI 2017
    • NIPS 2016
    • ICML 2015
    • NIPS 2015
    • NIPS 2014
    • NIPS 2013 (reviewer award)