Gregory J. Herschlag, Associate Research Professor

Gregory J. Herschlag

I am interested in studying techniques to understand fairness in redistricting.  I am also interested in computational fluid dynamics and high-performance computing.

Office Location:  207 Physics
Office Phone:  919-660-2861
Email Address: send me a message
Web Page:  https://sites.duke.edu/quantifyinggerrymandering

Teaching (Spring 2024):

Teaching (Fall 2024):

Education:

Ph.D.University of North Carolina, Chapel Hill2013
Keywords:

Computational fluid dynamics • Computational methods in Markov chains • Fairness • Gerrymandering • High performance computing--Research • Lattice Boltzmann methods • Redistricting • Sampling (Statistics)

Recent Publications

  1. Autry, E; Carter, D; Herschlag, GJ; Hunter, Z; Mattingly, JC, METROPOLIZED FOREST RECOMBINATION FOR MONTE CARLO SAMPLING OF GRAPH PARTITIONS, SIAM Journal on Applied Mathematics, vol. 83 no. 4 (August, 2023), pp. 1366-1391 [doi]  [abs]
  2. Zhao, Z; Hettle, C; Gupta, S; Mattingly, JC; Randall, D; Herschlag, GJ, Mathematically Quantifying Non-responsiveness of the 2021 Georgia Congressional Districting Plan, ACM International Conference Proceeding Series (October, 2022), ISBN 9781450394772 [doi]  [abs]
  3. Herschlag, G; Lee, S; Vetter, JS; Randles, A, Analysis of GPU Data Access Patterns on Complex Geometries for the D3Q19 Lattice Boltzmann Algorithm, IEEE Transactions on Parallel and Distributed Systems, vol. 32 no. 10 (October, 2021), pp. 2400-2414 [doi]  [abs]
  4. Autry, EA; Carter, D; Herschlag, GJ; Hunter, Z; Mattingly, JC, METROPOLIZED MULTISCALE FOREST RECOMBINATION for REDISTRICTING, Multiscale Modeling and Simulation, vol. 19 no. 4 (January, 2021), pp. 1885-1914, Society for Industrial & Applied Mathematics (SIAM) [doi]  [abs]
  5. Herschlag, G; Mattingly, JC; Sachs, M; Wyse, E, Non-reversible Markov chain Monte Carlo for sampling of districting maps (August, 2020)  [abs]