Jonathan Michala's Personal Website

Education

University of Southern California, Ph.D. Mathematics, Provost Fellow (May 2025)
Advisor: Kyler Siegel

Duke University, B.S. Mathematics, Magna Cum Laude (May 2020), Minor in Computer Science
U.S. Presidential Scholar

Bio

Jonathan is a research manager at the ML Alignment & Theory Scholars (MATS) program, where he offers support for strong research outputs and scholar outcomes in AI Safety. Previously, he earned his PhD in mathematics from the University of Southern California where he completed his thesis on embedding problems in symplectic geometry.

Activities

• SPAR - Supervised Program for Alignment Research, participant - Spring 2025
  Optimal Collective Intelligence Control
  Mentors: Jonas Hallgren and Aaron Halpern with Equilibria Network
  Geometry of Spacial World Models
  Mentor: Matthieu Moullec
• UC Riverside Geometry-Topology Seminar, speaker - February 2025
  Title: Obstructions to Symplectic Embeddings in Dimension at least 6
• AI Safety Fundamentals Alignment Course, participant - Fall 2024
  Instructor: Chris Ackerman
  Project: Introduction to the Learning Theoretic Agenda (Agent Foundations)
• Math Department Coding Group, project lead - Fall 2024, USC
  Lecture transcription tool, joint with Tianle Liu
• AI Safety Club Collaboration, contributor - Fall 2024 to Spring 2025, USC
  Using Microsoft Trace for autoformalization in Lean, joint with Oliver Liu and AJ Mannan
• Qualifying Exam Boot Camp, Instructor - Summer 2024, USC
  Taught Algebra, Real Analysis, and Topology
• Kylerec Workshop, speaker - Summer 2024, Easton, WA
  Title: The Cluster Formalism
  Reference: Ionel-Parker 2018. The Gopakumar-Vafa formula for symplectic manifolds
• SFT Zoom Reading Group, Organizer - Fall 2023 to Spring 2024
  Text: Wendl, Lectures on Symplectic Field Theory
  joint with Johannes Hauber, Filip Strakos, Matthew Buck, and Adrian Dawid
• Graduate Colloquium Speaker - Fall 2023, USC
  Title: Introduction to Symplectic Geometry and Floer Homology
• Permutation Patterns Conference, Poster Presenter, - Summer 2023, Dijon, France
  Poster: Characterizing Rothe Diagrams, joint with Ben Gillen
• Persistence Homology Conference, attendee - Summer 2023, Albi, France
  Topic: persistence homology in symplectic and contact topology
• Floer Homology and Symplectic Homology Reading Group, organizer - Spring 2023
  Texts: Audin-Damian, Wendl, Oancea, Floer-Hofer-Wysocki
• Combinatorics Seminar, speaker - Spring 2023, USC Title: Characterizing Rothe Diagrams, joint with Ben Gillen
• Morse Theory Reading Group, organizer - Fall 2021, USC
  Text: Audin-Damian
• Duke University Union Freewater Productions, chair - Fall 2019 to Spring 2020
  Led Duke’s student film production house
• U.S. Senate, intern - Summer 2017, Washington D.C.
  Office of Senator Tim Scott
• South Carolina Youth in Government, Youth Governor - Fall 2015
  Elected to lead mock government for high school students across South Carolina
• Eastside High School, Student Body President - 2015 to 2016, Greenville, SC
  Raised $125,000 for the With Purpose Foundation

Publications

• Jonathan Michala. Refined Elementary Capacities from Symplectic Field Theory. 2025. Dissertation.
• Ben Gillen and Jonathan Michala. Characterizing Rothe Diagrams, 2023. Preprint.
• Jonathan Michala, Alexander Pierson, Terry A. Loring, and Alexander B. Watson. Wave-packet propagation in a finite topological insulator and the spectral localizer index, Involve, 2021.
• Jonathan Michala. The ranked pairs voting method and its properties: Findings and a conjecture, 2020. Undergraduate honors thesis.

Teaching

• Graduate Algebraic Combinatorics, Grader - Fall 2024
• Calculus III, Teaching Assistant, - Spring 2022
• Calculus II, Teaching Assistant, - Fall 2021
• Business Calculus, Teaching Assistant, - Spring 2021

Service

• Math Graduate Student Association, President - Fall 2022 to Spring 2023, USC
• Alumni Industry Panel, Organizer - Fall 2022, USC
• Directed Reading Program, Mentor - 2022, USC
  • Mentee: Jarret Spino
    Text: LinSyn: Synthesizing Tight Linear Bounds for Arbitrary Neural Network Activation Functions by Brandon Paulson and Chao Wang
  • Mentee: Serena Yang
    Text: An introduction to Topological Data Analysis: fundamental and practical aspects for data scientists by Frédéric Chazal and Bertrand Michel
  • Mentee: Olivia Lin
    Text: An Introduction to Mathematical Cryptography by Silverman, Pipher, and Hoffstein
  • Mentee: Aaron Andrews
    Texts: Algebraic Topology by Hatcher, and Introduction to Smooth Manifolds by Lee