- Ali Rejali — Probability theory and additive number theoretic functions (Stanford)
- Richard Greer — Consistent nonparametric estimation of best linear classification rules: Solving inconsistent systems of linear equalities (Stanford)
- Arif Zaman — Finite forms of de Finetti's theorem of Markov chains (Stanford)
- Hani Doss — Bayesian nonparametric estimation of location (Stanford)
- Douglas Critchlow — The metric method for partially ranked data (Harvard)
- Peter Matthews — The waiting time to cover a group in random walk (Stanford)
- Richard Deveaux — The mixture of normal regression problems (Stanford)
- Alex McMillan — Robustness of the James-Stein estimator (Stanford)
- Andrew Greenhalgh — Probability measures with subgroup invariance properties (Stanford)
- Daniel Rockmore — Fast Fourier analysis for finite groups (Harvard)
- Robin Pemantle — Random walk with reinforcement (MIT)
- Martin Hildebrand — Rates of convergence of some random processes on finite groups (Harvard)
- Anil Gangolli — Convergence bounds for Markov chains and applications to sampling schemes (Stanford)
- Eric Belsley — Rates of convergence of Markov chains related to association schemes (Harvard)
- Jeffrey Rosenthal — Rates of convergence for Gibbs sampler and other Markov chains (Harvard)
- Carl Dou — Studies of random walks on groups and random graphs (MIT)
- David Maslen — Fast transforms and sampling for compact groups (Harvard)
- Eric Rains — Topics in probability on compact Lie groups (Harvard)
- Francis Su — Measuring rates of convergence of random walks on groups (Harvard)
- David Steinstaltz — Socks and boxes: Variations on Bernoulli's marriage problem (Harvard)
- Brad Mann — A Berry-Esseen theorem for Markov chains (Harvard)
- Farid Bassiri — Random walks on groups with multiplicity two (Harvard)
- Jeffrey Silver — Rates of convergence in the Metropolis algorithm (Harvard)
- Nathan Lulov — Random walk on involutions (Harvard)
- Jason Fulman — Probability in the classical groups over finite fields (Harvard)
- Igor Pak — Random walk on groups: Strong uniform time approach (Harvard)
- Kelly Wieand — Eigenvalue distributions of random matrices in the permutation group and compact Lie groups (Harvard)
- Elizabeth Wilmer — Rate of convergence for some non-reversible Markov chains (Harvard)
- Asya Takken — Monte Carlo goodness-of-fit tests of discrete data (Stanford)
- Thomas Yan — A rigorous analysis of the Creutz Demon algorithm for the microcanonical, one-dimensional Ising model (Cornell)
- Jay-Calvin Uyemura-Reyes — Random walk, semi-direct products and card shuffling (Stanford)
- Marc Coram — Bayesian nonparametric discrimanent analysis (Stanford)
- Arnab Chakrabourty — An attempt at optical character recognition for the Bengali language (Stanford)
- Sourav Chatterjee — Concentration inequalities with exchangeable pairs (Stanford)
- Joseph Blitzstein — From characterization to algorithm (Stanford)
- Elizabeth Meckes — An infinitesimal version of Stein's method (Stanford)
- Daniel Ford — The alpha model for phylogenetic trees (Stanford)
- Julia Salzman — Spectral analysis for discrete data using Markov chains (Stanford)
- Geir Helliloid — Enumerative theory of automorphisims of finite p-groups (Stanford)
- Hua Zhou — Topics on Markov chains with polynomial eigenfunctions (Stanford)
- Kshitij Khare — Extension of Dynkin's and Diaconis-Evans' constructions of Gaussian fields from Markov processes, etc. (Stanford)
- Olena Bormishenko — Random walk on the permutation group (Stanford)
- Sukhada Fadnavis — Graph coloring and birthday problems (Stanford)
- John Jiang — Markov chains and algorithms (Stanford)
- Aaron Smith — Coupling bounds for Markov chains (Stanford)
- James Zhao — A random walk through combinatorial probability (Stanford)
- Amy Pang — Hopf algebras and Markov chains (Stanford)
- Sumit Mukherjee — Estimation in exponential families with unknown normalizing constant (Stanford)
- Megan Bernstein — Random walks on the symmetric group, likelihood orders, and involutions (Stanford)
- Evita Nestoridi — Rates of convergence of Markov chains to stationarity, strong stationary times, coupling, Gelfand pairs and comparison theory (Stanford)
- Bhaswar Bhattacharya — Power of graph-based two-sample tests (Stanford)
- Bobbie Glen Chern — Large deviations approximation to normalizing constants in exponential models (Stanford)
- Daniel Jerison — The drift and minorization method for reversible Markov chains (Stanford)
- Amir Sepehri — Nonparametric goodness-of-fit testing and applications (Stanford)
- Graham White — Combinatorial methods in Markov chain mixing (Stanford)
- Paulo Orenstein — Topics in robust mean estimation (Stanford)
- Andy Tsao — New algorithms for simulating from difficult combinatorial problems (Stanford)
- Guanyang Wang — Topics in Markov chain simulation methods with applications in statistics (Stanford)
- Chenyang Zhong — Mallows permutation model: Sampling algorithms and probabilistic properties (Stanford)
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