About Me

    Michael
  • I am a waning first year PhD student at the University of Washington, advised by Paul Beame and Anup Rao. Prior to that, I completed my MS at UC Berkeley working with Professor Avishay Tal. I am broadly interested in theoretical computer science, but have a particular affinity for property testing, Boolean function analysis, and complexity theory.
  • Outside of school, I am particularly fond of ping pong and racket sports, having been president of Cal's table tennis club (CalTTC) and done a bit of competing myself. I also enjoy climbing, soccer, and wake/snowboarding! I also like board games and escaping from rooms.

  • Email: mdwhit (at) cs (dot) washington (dot) edu

Research

For everything, see my Google Scholar.

  • Junta Distance Approximation with Sub-Exponential Queries (link)
    • joint work with Vishnu Iyer and Avishay Tal
    • Ever wondered how many (input, output) pairs from your function f you have to look at to estimate how close f is to only depending on a few of its inputs? So did we. This work gives an improved algorithm for answering this question for Boolean functions. If you are really interested in questions like this, you can check out my master's thesis, which starts with a survey of the previous work done on junta testing and (almost) all its variants.
    • Here's a talk I gave: link and here is slightly more detailed talk that Avishay gave: link
  • Searching for Regularity in Bounded Functions (link)
    • joint work with Siddharth Iyer
    • We spent some time trying to find subspaces for which bounded functions become pseudorandom.
  • Teaching

    • Berkeley:
      • I spent most of my teaching energy at Berkeley as (head) TA for Berkeley's course on probability and stochastic processes, EECS 126. I typed up some notes for the class, but they are most certainly far from perfect.
    • Washington:
      • CSE 431: (Spring 2022) Intro to Theory of Computation.

    Older Projects

    Before I became interested in theory, I dabbled in projects on islanding in energy grids, battery life maximization, and regression for biological datasets.

    • Islanding and Self-Sufficiency of Block-Scale Microgrids link
      • Aminy Ostfeld, Michael Whitmeyer, Alexandra Von Meier
      • IEEE Green Technologies Conference (2018)

    • EcoBlock: Grid Impacts, Scaling, and Resilience link
      • Aminy Ostfeld, Alexandra Von Meier, Michael Whitmeyer, Mohini Bariya
      • Full Report

    • Reinforcement Learning-based Fast Charging Control Strategy for Li-ion Batteries link
      • Saehong Park, Andrea Pozzi, Michael Whitmeyer, Hector Perez, Won Tae Joe, Davide M Raimondo, Scott Moura
      • 2020 IEEE Conference on Control Technology and Applications (CCTA)

    Miscellaneous

    • Discrepancy Minimization, a writeup on recent developments in algorithmic discrepancy minimization. Final Project for CS270 (Combinatorial Algorithms).
    • Battery Life Utilizes LSTMs and Attention to predict the useful life of batteries. Final Project for CS182 (Deep Learning).
    • Measurement-Based QC A writeup on various techniques for Measurement-Based Quantum Computing as well as few more recent results/implications.
    I also started a blog recently, which you can find here. I plan on just talking about theoretical computer science and life there.
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