Statistics Faculty Research Interests

The statistics faculty research interests cover a wide range of topics in both statistics and probability. 

Sandra Cerrai

Stochastic analysis, Stochastic partial differential equations, Probabilistic methods for PDEs in finite and infinite dimension

Dmitry Dolgopyat

Dynamical Systems, Averaging Theory, Transport in Random Media

Mark I. Freidlin

Stochastic Processes and Their Applications, Random Perturbations of Dynamical Systems, Probabilistic Methods in P.D.E.'s and Analysis

Abram Kagan

Characterization Problems, Estimation Theory, Semi-Parametric Models

Benjamin Kedem

Time series, Semiparametric inference, Generalized Linear Models, Statistics of space-time observations, Spatial prediction, Zero-crossings

Leonid Koralov

Stochastic processes and applications, Branching processes, Asymptotic analysis of probabilistic models

Yuan Liao

Econometric Theory, Bayesian asymptotics

Jian-Jian Ren

Survival Analysis and its Applications in Biomedical Research, Linear models, Likelihood methods, Resampling Methods, Analysis of Censored Data

Takumi Saegusa

Survival Empirical Process Theory, Semiparametric Models, Complex Sampling, Bootstrap

Eric V. Slud

Sample Survey Theory, Statistical Inference for Stochastic Processes, Survival Analysis

Paul J. Smith

Nonparametric and Robust Statistics, Categorical Data Analysis

Tingni Sun

High-dimensional statistical inference, Nonparametric Statistics, Sparse/Low-rank matrix problems

Grace Yang, Professor Emerita

Stochastic Modelling with Application to Biological and Physical Sciences, Asymptotic Theory in Statistics, Survival Analysis

The Mathematical Statistics Program of the University of Maryland offers degrees of Master of Arts and Doctor of Philosophy.

• Basic Information about the Mathematical Statistics Program
• Educational Policies of the Mathematical Statistics Program
• Statistics Faculty Research Interests
• List of Recent Ph.D.s in the Statistical Sciences
• Statistics Seminar
• Statistics Program Homepage

1. A graduate student may, upon the recommendation of the dissertation director, and with the endorsement of the home graduate program graduate director or chair, include his or her own published works as part of the final dissertation. Appropriate citations within the dissertation including where the work was previously published are required. All such materials must be produced in standard dissertation format.
2. It is recognized that a graduate student may co-author work with faculty and colleagues that should be included in a dissertation. In such an event, a letter should be sent to the Dean of Graduate Studies and Research certifying that the student's examining committee has determined that the student made a substantial contribution to that work. This letter should also note that inclusion of the work has the approval of the dissertation adviser and the program chair or graduate director. The format of such inclusions must conform to the standard dissertation format. A foreword to the dissertation, as approved by the Dissertation Committee, must state that the student made the substantial contributions to the relevant aspects of the jointly authored work included in the dissertation.

Effective immediately, the Foreign Language Exams are no longer a requirement for the Graduate Program.

Updated: 9/28/2020

Expectations

It is the student's responsibility to prepare for the topics on the syllabus for each individual exam. The courses do not usually cover all the material that is required for the written exams. Get the syllabi from the graduate office, and make sure you know what the requirements are to prevent unpleasant surprises.

It is expected that the problems that are handed in by the students should be written in a coherent manner, in enough detail to show that there is understanding and knowledge of the necessary concepts and techniques. It is not necessarily helpful to state any theorem and result that might be related in the slightest manner.

Guidelines for preparation for the written exams:

• Try to take the exams as early as possible. In particular, take an exam as soon as you finish the corresponding course sequence, or even while you are still taking the course sequence. You have nothing to lose (except your time and your pride) by taking the exams too early, but you have a lot to lose by putting them off.
• Get all the old exams, and TRY TO DO AS MANY PROBLEMS AS POSSIBLE. Get homeworks, notes and exams for the courses from other students and go over them.
• Form study groups. Prepare before you meet - don't waste your time. Talk to people in your courses; find out who signed up for the same exams as you did.
• Do not hesitate to ask faculty members for help if you get stuck studying.
• Try to start studying as early as October if you plan on taking the January exams. It is very hard to find enough time during a busy term, and also take into account that the holidays get in the way.
• Time yourself when you do old problems. On the exam you have 40 minutes for each problem, therefore it is helpful to practice under time restrictions.

Help on the www: Suggestions from Professor O'Leary in the CS Department