Eric Severson

Math Faculty

Proof School

I’m currently teaching math and computer science at Proof School in San Francisco.

I like making nice math visuals. Lately I’ve been making a lot of interactive things with Geogebra, as well as Desmos. Most recently I made a bunch of tools for a visually-driven Complex Analysis class, which I say more about in these slides from Gathering 4 Gardner 16.()

I also have a couple videos I made for the 3b1b Summer of Math Exposition.

Education

PhD in Applied Mathematics, 2021
UC Davis
BS in Applied Mathematics, 2016
UC Berkeley

Teaching

Courses taught at Proof School:

Exponents/Logs/Trig B: Blocks 3-4 2025-26, Block 4 2024-25, Block 4 2023-24, Block 4 2022-23
Stochastic Processes: Block 2 2025-26, Block 3 2021-22
Complex Analysis: Block 1 2025-26, Block 2 2023-24
Machine Learning: Year long 2024-25 and 2022-23
Dynamics of Differential Equations: Block 5 2024-25, Block 5 2022-23
Euclidean Geometry 1: Block 3 2024-25, Block 2 2021-22
Theory of Computation: Block 2 2024-25, Block 4 2021-22
Graph Theory 1: Block 1 2024-25, Block 1 2023-24
Mathematical Cryptography: Block 5 2023-24
Euclidean Geometry 2: Block 3 2023-24
Statistics A: Block 3 2022-23
Differential Calculus: Block 2 2022-23
Discrete Probability: Block 1 2022-23 and Block 1 2021-22
Cryptography: Block 5 2021-22

Courses taught as a full instructor at UC Davis:

Math 115A (Number Theory): Summer 2020
Math 145A (Combinatorics): Summer 2019
Math 21D (Vector Calculus): Fall 2018
Math 21C (Series and Partial Derivatives): Summer 2017

Courses taught as a teaching assistant at UC Davis:

ECS 220 (Graduate Theory of Computation): Spring 2020 and Spring 2021
ECS 289A (Molecular Computation): Winter 2021
Math 21D (Vector Calculus): Winter 2019
Math 135B (Stochastic Processes): Spring 2018
Math 21B (Integral Calculus): Winter 2018
Math 21A (Differential Calculus): Fall 2017
Math 135A (Probability): Fall 2017
Math 108 (Intro to Abstact Math): Winter and Spring 2017
Math 17C (Calculus for Biology): Fall 2016

Research

My PhD was in Applied Mathematics at UC Davis , working with professor David Doty. My research was at the intersection of distributed computing and molecular computing, focusing on the related models of population protocols and chemical reaction networks. These models describe a population of simple computational agents (ie. molecules) that have random pairwise interactions (ie. chemical reactions) and try to compute properties of the global configuration through these purely local interactions. Proving results in these models uses tools from theory of computation and stochastic processes.

David Doty, Eric Severson (2021). ppsim: A software package for efficiently simulating and visualizing population protocols. In CMSB 2021.

README for software package Full Paper on Arxiv

David Doty, Mahsa Eftekhari, Leszek Gąsieniec, Eric Severson, Grzegorz Stachowiak, Przemysław Uznański (2021). A time and space optimal stable population protocol solving exact majority.

Code Dataset Video Full Paper on Arxiv

Janna Burman, Ho-Lin Chen, Hsueh-Ping Chen, David Doty, Thomas Nowak, Eric Severson, Chuan Xu (2021). Time-optimal self-stabilizing leader election in population protocols. In PODC 2021.

Slides Video Full Paper on Arxiv

Talley Amir, James Aspnes, David Doty, Mahsa Eftekhari, Eric Severson (2020). Message complexity of population protocols. In DISC 2020.

Slides Video Full Paper on Arxiv

Eric Severson, David Haley, David Doty (2019). Composable computation in discrete chemical reaction networks. In DIST 2020 (Journal) and PODC 2019 (Conference).

Poster Slides Journal Publication Conference Publication Full Paper on Arxiv