The research of the faculty covers a broad area of probability theory, mathematical statistics, and their applications.

FACULTY

  1. Alexander, Kenneth: Probability models in statistical mechanics: lattice models (Ising model, Potts model, percolation, etc.), phase transitions, disordered models.
  2. Arratia, Richard: Probability, especially as related to combinatorics and number theory, coupling, and approximation.
  3. Baxendale, Peter [emeritus]: Stochastic dynamical systems; equilibrium, stability and bifurcation for solutions of stochastic differential equations; applications to stochastic neuronal models.
  4. Dimitrov, Evgeni: Integrable probability.
  5. Fulman, Jason: Markov chains, probability on algebraic structures, random matrix theory, Stein’s method.
  6. Goldstein, Larry: Distributional approximation and Stein’s method, high dimensional statistics, concentration inequalities, sampling schemes in epidemiology, statistical efficiency, optimal stopping.
  7. Lototsky, Sergey: Stochastic partial differential equations, optimal nonlinear filtering of diffusion processes, statistical inference for continuous-time processes.
  8. Lv, Jinchi (Marshall School of Business): statistics, machine learning, data science, business applications, and artificial intelligence and blockchain.
  9. Ma, Jin: Stochastic analysis, stochastic differential equations, stochastic control theory, mathematical finance and insurance.
  10. Mikulevicius, Remigijus (Remi): Stochastic differential equations, stochastic analysis.
  11. Minsker, Stanislav (Stas): Statistical learning theory, non-parametric statistics, concentration inequalities, mathematical finance.
  12. Sun, Fengzhu (Department of Quantitative and Computational Biology): Quantitative and computational biology, probability, statistics.
  13. Waterman, Michael [emeritus] (Department of Quantitative and Computational Biology): Molecular and computational biology, probability, statistics.
  14. Zhang, Jianfeng: Stochastic analysis, backward stochastic differential equations, stochastic numerics, and mathematical finance.

POST DOCS AND VISITORS

  • Ararat, Cagin: Vector-valued and set-valued functions in financial mathematics, optimization and stochastics.  Visiting Fulbright Scholar from Bilkent University (Turkey).
  • Gao, Lan: High-Dimensional Statistics, High-Himensional Inference, and Causal Inference.
  • Heilman, Steven: High-Dimensional Probability, Concentration Inequalities, Theoretical Computer Science, Random Graphs.
  • Ostrovskii, Dmitrii: Machine Learning, Statistics, Optimization, and Signal Processing.
  • Rychnovsky, Mark: Random Matrix Theory, Statistical Mechanics, and Kardar Parisi Zhang Universality, as well as combinatorics and epidemiology.
  • Zhang, Zhaoyu: Stochastic Analysis, Stochastic Control/Games, Mathematical Finance and Insurance.

CURRENT PhD STUDENTS

  1. Maria Allayioti (Goldstein)
  2. Atiqah Almuzaini (Ma)
  3. Aykut Arslan (Lv)
  4. Xinze Du (Lv)
  5. Thejani Gamage (Ma)
  6. Melih Iseri (Zhang)
  7. Abdullah Karakus (Alexander)
  8. Cora Liang (Goldstein/Sun)
  9. J.E. Paguyo (Fulman)
  10. Bixing Qiao (Zhang)
  11. Ying Tan (Ma)
  12. Lijia Wang (Goldstein)
  13. Bo Wu (Alexander)
  14. Shunan Yao (Minsker/Tong)

CURRENT MASTERS STUDENTS:

  1. Chuhuan Huang (Heilman)

CURRENT UNDERGRADUATE STUDENTS:

  1. Benny Cohen (Heilman)
  2. Jake Freeman (Heilman)

ACTIVITIES

RECENT Ph.D. GRADUATES, THEIR ADVISORS, AND DISSERTATIONS

2022

  • Liu, Jinting (Goldstein/Sun), Selective Inference With Confident Directions
  • Pollok, Austin (Zhang), High-Frequency Kelly Criterion and Fat-Tails: Gambling with an Edge
  • Shah, Apoorva (Lototsky), Gaussian Free Fields and Stochastic Parabolic Equations
  • Tarter, Alex (Goldstein/Heilman), Dimension Reduction Techniques for Noise Stability Theorems
  • Vossler, Patrick (Yingying Fan/Lv), Nonparametric Ensemble Learning and Inference
  • Wu, Yusheng (Lototsky/Tong), Asymptotic Properties of Two Network Problems with Large Random Graphs

2021

  • Feng, Pengbin (Ma/Zhang), Dynamic Network Model for Systemic Risk
  • Gangopadhyay, Ujan (Alexander), Fluctuations of the Transverse Increments in the Two-dimensional First-passage Percolation Model
  • Luo, Man (Ma), Topics on Dynamic Limit Order Book and its Related Computation
  • Rahmani, John (Fulman), Mixing Times for the Commuting Chain
  • Wang, Lang (Minsker), Robust Estimation of High Dimensional Parameters
  • Wu, Wenqian (Ma), Topics on Set-Valued Backward Stochastic Differential Equations
  • Zhu, Zimu (Zhang), Some Topics on Continuous Time Principal-Agent Problem

2020

  • Aronowitz, Julian (Bartroff), Finite Sample Bounds in Group Sequential Analysis via Stein’s Method
  • Phonsom, Chukiat (Mikulevicius), On Stochastic Integro-Differential Equations
  • Ruan, Jie (Zhang), Numerical Methods for High-Dimensional Path-Dependent PDEs Driven by Stochastic Volterra Equations
  • Wei, Xiaohan (Minsker/Neely), Part I: Asynchronous optimization over weakly coupled renewal systems. Part II: High dimensional estimation under weak moment assumptions
  • Wu, Hao (Zhang/Lv), Statistical Insights into Deep Learning and Flexible Causal Inference

2019

  • Demirkaya, Emre (Yingying Fan/Goldstein/Lv), Reproducible Large-Scale Inference in High-Dimensional Nonlinear Models
  • He, Xinrui (Bartroff), Asymptotically optimal sequential multiple testing with (or without) prior information on the number of signals
  • Ozdemir, Alperen (Fulman), On Limiting Distribution and Convergence Rates of Random Processes Defined Over Discrete Structures
  • Wiroonsri, Nathakhun (Goldstein), Steins’ Method via Approximate Zero Biasing and Positive Association with Applications to the Combinatorial Central Limit Theorem and Statistical Physics
  • Xu, Fanhui (Mikulevicius), On the parabolic Kolmogorov integro-differential equation and its applications

2018

  • Bhattacharjee, Chinmoy (Goldstein), Stein’s Method and its Applications in Strong Embeddings and Dickman Approximations
  • Kim, Gene B (Fulman), Distribution of Descents in Matchings
  • Kim, Hyun-Jung (Lototsky), Time-Homogeneous Parabolic Anderson Model
  • Noh, Eunjung (Ma), Equilibrium Model of Limit Order Book and Optimal Execution Problem
  • Ozel, Enes (Fulman), Cycle Structures of Permutations with Restricted Positions
  • Sun, Rentao (Ma), Conditional Mean-Field Stochastic Differential Equations and Their Applications
  • Wang, Jian (Lototsky), Statistical Inference For Second-Order Ordinary Differential Equation Driven by Additive Gaussian White Noise

2017

  • Hankin, Michael (Bartroff), Sequential Testing of Multiple Hypotheses With FDR Control Under Dependence
  • Nguyen, Dinh (Fulman), Random Walks on Finite Groups and Their Irreducible Representations
  • Wu, Cong (Zhang), Controlled McKean-Vlasov Equations and Related Topics
  • Xing, Xiaojing (Ma), Optimal Investment and Dividend under Sparre Andersen Model

2016

  • Kang, Yongjian (Lv/Zhang), Large-Scale Inference in Multiple Gaussian Graphical Models
  • Karnam, Chandrasekhar (Ma/Zhang), Dynamic Approaches for some Time Inconsistent Problems
  • Tsilifis, Panagiotis (Ghanem/Mikulevicius), Design, Adaptation and Variational Methods in Uncertainty Quantification
  • Xie, Weisheng (Ma), Stochastic Differential Equations Driven by Fractional Brownian Motion and Poisson Point Processes

2015

  • Keller, Christian (Zhang), Pathwise Stochastic Analysis and Related Topics
  • Ren, Haining (Fulman), Convergence Rates of i-Cycles After an m-Shelf Shuffle
  • Zhang, Tian (Ma), Optimal Investment and Reinsurance Problems and Related Non-Markovian FBSDEs With Constraints
  • Zheng, Zemin (Goldstein/Lv), High-Dimensional Latent Variable Thresholded Regression

2014

  • Daley, Timothy (Smith/Waterman), Non-Parametric Models For Large Capture-Recapture Experiments With Applications to DNA Sequencing
  • Bessam, Diogo (Lototsky), Large Deviations Rates in a Gaussian Setting and Related Topics
  • Ekren, Ibrahim (Zhang), Path-Dependent Partial Differential Equations and Related Topics
  • Islak, Umit (Fulman), Concentration Inequalities with Couplings from Stein’s Method
  • Sokolov, Grigory (Tartakovsky/Lototsky), Multi-Population Optimal Change-Point Detection
  • Zhuo, Jia (Zhang), Probabilistic Numerical Methods for Fully Nonlinear PDEs and Related Topics

2013

  • Chubatiuk, Alona (Schumitzky), Nonparametric Estimation of an Unknown Probability Distribution Using Maximum Likelihood and Bayesian Approaches
  • Marinov, Radoslav (Fulman), Applications of Stein’s Method on Statistics of Random Graphs
  • Pham, Triet (Zhang), Zero-Sum Stochastic Differential Games in Weak Formulation and Related Norms for Semi-Martingales
  • Pike, John (Fulman), Eigenfunctions for Random Walks on Hyperplane Arrangements
  • Song, Jinlin (Bartroff), Time-Sequential Testing for Multiple Hypotheses
  • Wang, Huanhuan (Ma), Asset Management with Incomplete Information
  • Wang, Xin (Ma), Nonlinear Expectations for Continuous Time Model with Jumps and Applications
  • Xu, Li (Lototsky), Parameter Estimate for Hyperbolic SPDE’s with Stochastic Coefficients
  • Yildirim, Gokhan (Alexander), On the Depinning Transition of the Directed Polymer in a Random Environment With a Defect Line
  • Zhong, Jie (Lototsky), Second Order in Time Stochastic Evolution Equation and Wiener Chaos Approach

2012

  • DeSalvo, Stephen (Arratia), Probabilistic Divide-and-Conquer – A New Methods for Exact Simulation – and Lower Bound Expansions for Random Bernoulli Matrices via Novel Integer Partitions
  • Du, Jie (Zhang), Stochastic Games on Stopping Times
  • Ghosh, Subhankar (Goldstein), Couplings for Berry-Esseen Bounds and Concentration Inequalities
  • Kaligotla, Sivaditya (Lototsky), Asymptotic Problems in Stochastic Partial Differential Equations: A Wiener Chaos Approach
  • Lin, Ning (Lototsky), Estimation of Coefficients in Stochsatic Differential Equations
  • Moers, Michael (Lototsky), Statistical Inference of Stochastic Differential Equations Driven by Gaussian Noise
  • Nibert, Joel (Baxendale), Invariant Measures of a Stochastic Predator-Prey Model
  • Xu, Shanshan (Lototsky/Wilcox), Initiative Non-Parametric Multivariate Regression Hypothesis Testing

2011

  • Chen, Jianfu (Ma), Regime Switch Term Structure model with Forward-Backward Stochastic Differential Equations
  • Lin, Wei (Goldstein), Survival Analysis With Missing Data and High Dimensionality
  • Wang, Xinyang (Ma/Zhang), Dynamic Model for Limit Order Books and Optimal Liquidation Problems
  • Yun, Youngyun (Ma), Analysis of Correlated Defaults and Joint Default Probability in a Contagion Model

2010

  • Liu, Wei (Lototsky), Statistical Inference for Stochastic Hyperbolic Equations
  • Zhang, Changyong (Mikulevicius), Numerical Weak Approximation of Stochastic Differential Equations Driven by Levy Processes

2009

  • Knape, Mathias (Mikulevicius/Zapatero), A General Equilibrium Model for Exchange Rates and Asset Prices in an Economy Subject to Jump-Diffusion Uncertainty
  • Pehlivan, Lerna (Fulman), On Top to Random Shuffles, no Feedback Card Guessing and Fixed Points of Permutations
  • Polunchenko, Aleksey (Mikulevicius/Tartakovsky), Quickest Change Detection with Applications to Distributed Multi-Sensor Systems
  • Ross, Nathan (Fulman), Exchangeable Pairs in Stein’s Method of Distributional Approximation

 

THE (FIRST) JOBS OF SOME OF OUR RECENT Ph.D. GRADUATES

2022

  • Austin Pollok: Assistant Professor of Clinical Data Science and Operations, USC
  • Apoorva Shah: Data Scientist at Neal Analytics
  • Alex Tarter: Statistician at the NASS (USDA)
  • Patrick Vossler: Postdoctoral Scholar, Stanford University

 

2021

  • Pengbin Feng: Research Scientist at Amazon.
  • Ujan Gangopadhyay: Postdoc at Natl. Univ. of Singapore.
  • Man Luo: Quant Researcher at Guotai Junan Securities Asset Management (Shanghai, China).
  • John Rahmani: Data Scientist at Accenture (San Diego, CA).
  • Wenqian Wu: Quant Trader at Guotai Junan Securities (Shanghai, China).
  • Zimu Zhu: Postdoc at UCSB.

2020

  • Julian Aronowitz: Data Scientist at Palo Alto Networks
  • Chukiat Phonsom: Alexandria Technology, Research and Investment
  • Jie Ruan: Facebook
  • Xiaohan Wei: Facebook

2019

  • Emre Demirkaya: Assistant Professor at the Haslam College of Business, University of Tennessee
  • Xinrui He: Statistician at Acumen/The SPHERE Institute
  • Alperen Ozdemir: Postdoc, Department of Mathematics, Georgia Tech
  • Fanhui Xu: Postdoctoral Associate, Carnegie Mellon University
  • Nathakhun Wiroonsri: Instructor, King Mongkut University of Technology Thonburi (Bangkok, Thailand)

2018

  • Chinmoy Bhattacharjee: Postdoc, IMSV, University of Bern
  • Gene Kim: Lecturer, USC; currently Lecturer at Stanford
  • Hyun-Jung Kim: Postdoc, Illinois Institute of Technology
  • Eunjung Noh: Hills Assistant Professor, Rutgers Univ
  • Enes Ozel: Adjunct Assistant Professor, UCLA
  • Rentao Sun: Data scientist, The Data Incubator

2017

  • Michael Hankin: Google
  • Dinh Nguyen: Polytechnic School (Pasadena)
  • Cong Wu: Quantitative Associate at Wells Fargo
  • Xiaojing Xing: Wells Fargo (Charlotte, NC)

2016

  • Yongjian Kang: Google
  • Chandrasekhar Karnam: Morgan Stanley
  • Panagiotis Tsilifis: Postdoc in the Viterbi School of Engineering at USC
  • Weisheng Xie: Wells Fargo (Charlotte, NC)

2015

  • Christian Keller: Postdoc at the University of Michigan
  • Haining Ren: Pixalate (Santa Monica, CA)
  • Tian Zhang: Education Management Systems
  • Zemin Zheng: Assistant Professor at the Chinese University of Science and Technology

2014

  • Diogo Bessam: Postdoc at PUC-RJ/IMPA (Brasil)
  • Ibrahim Ekren: Postdoc at ETH Zurich
  • Umit Islak: Postdoc at the University of Minnesota – Twin Cities
  • Grigory Sokolov: Postdoc at SUNY Binghamton
  • Jia Zhuo: Morgan Stanley

2013

  • Alona Chubatiuk: Postdoc at Children’s Hospital LA
  • Triet Pham: Postdoc at Rutgers
  • John Pike: Postdoc at Cornell
  • Jinlin Song: Researcher at the Analysis Group
  • Huanhuan Wang: Capital One
  • Xin Wang: Morgan Stanley
  • Li Xu: Google
  • Gokhan Yildirim: Lecturer at USC
  • Jie Zhong: Postdoc at Ritsumeikan University (Japan); currently Assistant Professor at Cal State LA

2012

  • Stephen DeSalvo: Postdoc at UCLA; currently at Google
  • Jie Du: Guggenheim Partners
  • Subhankar Ghosh: SAS Statistical Software
  • Sivaditya Kaligotla: Bloomberg LP
  • Ning Lin: Citigroup
  • Michael Moers: Deutsche Bank
  • Joel Nibert: Lecturer at USC

2011

  • Jianfu Chen: Union Bank of California
  • Wei Lin: Postdoc at UPenn
  • Xinyang Wang: Morgan Stanley
  • Youngyun Yun: Union Bank of California

2010

  • Wei Liu: American Express
  • Changyong Zhang: Postdoc at Salzburg University

2009

  • Mathias Knape: Goldman Sachs
  • Lerna Pehlivan: Lecturer at York University
  • Aleksey Polunchenko: Postdoc at USC
  • Nathan Ross: Postdoc at UC Berkeley