This lists students who worked with me on research. To find manuscripts and publications related to the projects listed below and which I coauthored, visit my Research & Publications page.


  • Ningwei Jiang (expected 2023). Working title: Characterization of Quasistationary Distributions for Markov Chains.
  • SangJoon Lee (2019): Asymptotic Analysis of Quasi-limiting Behavior for Drifted Brownian Motion Conditioned to Stay Positive. Thesis.
  • Hugo Panzo (2018): Scaling limits for Brownian Motion Penalized by its running maximum. Thesis.

UConn Undergrads (SURF Grant / Honors / Senior Thesis / Other) 

  • Mason Dicicco (Spring 2020), On Efficiency of Markovian Couplings (part of Markov Chains REU 2018). Poster presented in 22nd Frontiers UG Research Exhibition 2019.
  • Trajan Murphy (Spring 2019), School Policy Evaluated with Time-Reversible Markov Chains. Poster presented in 22nd Frontiers UG Research Exhibition 2019.
  • Dennis Scheglov (2018). I was the math co-advisor for Dennis’ University Scholars project.
  • Joseph Sweeney (Spring 2018): Nonexistence of Efficient Markovian Coupling for Finite State Markov Chains. Thesis.
  • Sailesh Simhadri  Spring 2018: Information Theory for Conditioned Markov Chains (research supported by UCONN SURF grant). Poster presented in Frontiers UG Research Exhibition, 2018.
  • Rachel Lonchar (Summer  2018): Nonexistence of Efficient Markovian Coupling for Finite State Markov Chains (research supported by UCONN SURF grant)
  • Thomas Bassine (Spring 2016): Stein’s Method.
  • Elizabeth Tripp (Spring 2015): Efficient Coupling for Random Walk with Redistribution (research supported by UCONN SURF grant), Honors thesis.

Markov Chains REU Students


  • Alan Boles (University of Tennessee, Knoxville), Leila Dahlia (University of Illinois, Chicago), Scott McIntyre (University of California, Berkley), Bronson Zhou (University of Texas, Austin): An Implementation of  a Maximal Coupling Algorithm for Markov Chains.
  • Gabe Cantanelli (U Texas, Arlington): Sampling Minimal Quasi-Stationary Distributions through a Renewal Formula
  • Bram Silbert (Wesleyan U), Lillian (Ian) Makhoul (Lehigh University): Coalescing Random Walks


  • Clay Allard (University of Utah), Shrikant Chand (New York University) and Julia Shapiro (University at Buffalo): Quasistationary Distributions for the Invasion and Voter model
  • Chris Vairogs (University of Florida) and Daniel Zou (Reed College): Coalescing and Annihilating Random Walks
  • Connor Bass (Macalester College),  Na’ama Nevo (Colorado College),  Caitlyn Powell (U of Alabama): Ballistic Deposition Model


  • Aenea Ferguson (Whitworth College),  Jack Hanke (UConn): Maximal Couplings for Finite State Markov Chains
  • Van Hovenga (U of Colorado Colorado Springs), Edith Lee (U of Rochester):
  • Ruoyu Lin (Boston U), Josh Speckman (USC): Self-Similar Structure in an Exchangeable Model for Population Dynamics


  • Jonah Green (Lehman College, CUNY), Taylor Meredith (NYU), Xioran (Rachel) Tan (UConn): Elephant Random Walks
  • R. Oliver VanderBerg (Kenyon College), Phil Speegle (U Alabama): Quasistationary Distribution for the Voter Model on the Complete Bipartite Graph.
  • Jonah Botvinick-Greenhouse (Amherst College), Mark Kong (Harvard), Connor Fitch (Bowdoin College): Nonlinear Random walk.

Mini projects: Inequalities in Probablity, Animated Logo (Connor Finch and Taylor Meredith), First Species Counterpoint Using Glouber Dynamics (Jonah Botvinick Greenhouse, Rachel Tan and Oliver Vanderberg), Optimization using the Metropolis-Hastings Algorithm (Philip Speegle), 15 Puzzle Solver (Mark Kong)


  • Carter Bedsole (George Fox U), Grace O’Neil (UPenn):  Biological Evolution Models Exhibiting Power Law Tails.
  • Mason DiCicco (UCONN), Michael Dotzel (U Missouri),  Ewan Harlow (U Wisconsin) Efficient Markovian Couplings.
  • Emily Gentles (U Arkansas), Natalie Meacham (Bryn Mawr), Erica West (Colorado School of Mines): Memory in Random Sequences.