General Information

Email Address


  • 2022 - 2026
    PhD, Electrical and Camputer Engineering
    University of Michigan, Ann Arbor, Michigan
    • GPA 3.93
    • Signal and Image Processing and Machine Learning
    • Co-advised by Dr. Clayton Scott and Dr. Angela Violi
    • Emphasis on computational chemistry and Machine Learning theory
    • Thesis Topic: Inverse Design of Nanoparticles from Small Datasets
  • 2020 - 2022
    MSc, Computer Science
    University of Michigan, Ann Arbor, Michigan
    • GPA 3.91
    • Member of the VioliGroup computational biochemistry lab (3 semesters, 2 summers)
    • President of the Machine Learning Theory Reading Group, 1 semester
  • 2016 - 2020
    BSc, Computer Science
    Chapman University, Orange, California
    • GPA 3.86
    • Member of the Provost List, 8 semesters
    • Recipient of the Chancellor’s Scholarship, 8 semesters
    • Tutor and Supplemental Instructor for Computer Science and Math, 4 semesters


  • 2023 - 2024
    Managing the Signal Processing in EECS (SPEECS) Seminar
    University of Michigan
  • 2023
    Textbook Editing for Upcoming Signal Processing Textbook
    University of Michigan, Jeffery Fessler
    • Verified and re-derived assertions and theorems
    • Validated references to existing literature
    • Suggested textual/minor structural changes to improve comprehension
    • Catching LaTeX typesetting errors
  • 2021 - 2022
    Directed Study and Summer Research
    University of Michigan, Angela Violi and Clayton Scott
    • Performed novel research in generalized molecular representations
    • Advised computational biochemists on machine learning methodology and literature
    • Supervised student researchers; Geometric Deep Learning and Deep Gaussian Processes
  • 2020
    Graduate Research Assistant
    University of Michigan, Mania Meibody
    • Developed platform for remote presentation and "workshopping" of 3d architectural models using JavaScript, SASS, NodeJS, BabylonJS, and SQL
    • Implemented Python scripts for automated 3D model compression
    • Performed literature reviews of existing software and wrote grant proposals
  • 2019
    Instrument Programmer
    Lotus Instruments
    • Developed controls for government-contracted, custom gas chromatography instruments
    • Analyzed documentation to create custom libraries for serial data transfer
  • 2019
    Software Engineering Intern
    Toyoda Gosei
    • Saved 2,000 man-hours and $60,000 per year through automated puchase order tracking
    • Implemented a web-based asset tracking software using full-stack ASP.NET
    • Collaborated with Cost Management to solidify requirements and return on investment


  • 2022 - 2023
    The Implicit Bias of Gradient Descent on Separable Multiclass Data
    • Developed a conjecture for extending existing work to include certain groups of multiclass losses
    • Showed numerically that our conjecture holds for certain well-known loss functions
    • Currently working on a proof for this general case
  • 2021
    DJGrad: Real-Time Distributed Learning in Connected and Autonomous Vehicles (CAVs)
    • Designed distributed learning protocol for sparse gradient propagation
    • Implemented simulated learning environment in Tensorflow
    • Demonstrated superior generalization, with fewer assumptions than Federated Learning
  • 2020
    Domain Exploration Through Artificial Curiosity
    • -Developed simulated Martian terrain as a domain - Beginning with Shmidhuber’s theoretical basis for artificial curiosity, developed an implementation using convolutional auto-encoders - Defined heuristic "Explorational Value" for evaluating path explored by model - Performed evaluation against naive models to illustrate effectiveness of artificial curiosity
  • 2020
    Needlecast: On-the-Fly Reconfiguration of Spacecraft Flight Software
    • Collaborated with NASA staff to draft specifications for protocols
    • Designed a library for booting NASA core Flight System (cFS) applications on-the-fly
    • Implemented Needlecast as a plug-and-play header file for NASA core cFE
    • Developed a simulated network switch and web interface for straightforward debugging
  • 2020
    AI-Driven Contemporary Archaeology for The International Space Station
    • Analyzed project requirements with Dr. Walsh (co-PI of ISS Archeology)
    • Compiled facial training dataset for 240 ISS astronauts
    • Utilized convolutional neural networks to label astronauts’ faces in NASA photo archives

Academic Interests

  • Inverse design
  • Nanochemistry
  • Geometric Deep Learning

Other Interests

  • Differential Geometry
  • Group Theory
  • Aerospace
  • Astronomy
  • Computer Graphics