Teaching
 I was on the faculty for the 2019 Voting Rights Data Institute where I:
 coled independent research groups
 Investigating locality splitting
 Hackathon for education
 Optimal transport distances between districting plans
 coled a workshop introducing topics in optimization
 Greedy Algorithms
 Dynamic Programming
 Linear and Integer Programming
 Optimal Transport
 gave tutorials on Python and gerrychain
 I was a graduate TA for Bo Waggoner's course Algorithmic Game Theory (NETS 412) in Spring 2018
 I was a graduate TA for Michael Kearns' course Networked Life (NETS 112) in Fall 2017
 I was a TA/grader/tutor at Colby College for:
 Calculus (MA121, 122)
 Micro and Macro Economic Principles/Theory (EC133, 134, 223, 224)
 Game Theory (EC379)
 Introductory Statistics (SC212, 231)
 Computational Thinking (CS151/152)
Notes

Notes for Theory of Computation (UPenn CIS 511, Spring 2017)

Notes for the pointset portion of Topology (UPenn Math 500, Fall 2017)

Notes from the Metric Geometry and Gerrymandering Group’s August 2017 Conference. Videos of the talks can be found on the MGGG YouTube channel
Talks

Algorithms for Applied LargeScale Differential Privacy. Written Preliminary Exam Presentation, October 2020.

Algorithms, Fairness, and Redistricting. Penn CIS Student Colloquium, April 2020.

TradeOffs in Fair Redistricting. AIES, February 7, 2020. [sildes]

Equilibrium Characterization for Data Acquisition Games. IJCAI, August 8, 2019. [slides]

Introduction to the Metagraph of Districting Plans. Voting Rights Data Institute, June 18, 2019.

Graphs, Geometry, and Gerrymanders. University of Toronto Dept. of Mathematics Diet Graduate Seminar, Feb. 21, 2019. [slides].

Shape Analysis for Redistricting. University of Toronto Dept. of Mathematics Hyperbolic Lunch Seminar Feb. 21, 2019. [slides].