Faculty & Staff

CMDA Administration

Program Leader, Division of Computational Modeling and Data Analytics

Mark Embree

Mark Embree, Program Leader

Professor of Mathematics
Associate Director, Virginia Tech Smart Infrastructure Laboratory

Email: embree@vt.edu
Phone: 540-231-9592


Carrie Hopkins

Academic Advisor,
Academy of Integrated Science

Email: carrieh7@vt.edu
Phone: 540-231-2442

charlotte parks

Charlotte Parks

Recruiter and Academic Advisor
Email: crobrtz@vt.edu
Phone: 540-231-8131


Cara Conley

Academic Advising and Enrollment Manager
Email: cara1@vt.edu
Phone: 540-231-8132

Connect with your CMDA advising team

On our advising website, you can find force add information, our scheduling system to schedule a meeting with one of us, and advising assignments so you know who your advisor is!

Core and Affiliated Faculty

My research is based in dynamical systems and control theory, with a focus on multi-agent systems and their collective behavior. In this context, I am interested in biologically-inspired mathematical modeling, studying models from both analytical and numerical perspectives, and developing applications informed by the results, such as robotic systems inspired by animal swarms and brain network control systems.

Much of my recent work tackles modeling of collective behavior in animal groups, which has included the motion of bats in flight and collective sensing through shared sonar within robotic swarms.

My work uses a wide range of methods, including: agent-based models which can be studied through numerical simulation; network models whose salient characteristics can be computed analytically; and data-driven analyses with which hypotheses on interaction network structures can be statistically tested.

Email : nabaid@vt.edu
Phone: 540-231-5516

Dr. Beattie's research interests include model reduction of large scale dynamical systems, computational linear algebra, spectral estimation for linear operators, and problems related to data assimilation and inference in oceanography and atmospheric sciences. 

Assistant Professor, University Libraries

Dr. Brown's research involves the application of computational molecular modeling and bioinformatic tools to relate the structure and dynamics of molecular systems to function. Currently, we study the amyloid β-peptide that is associated with Alzheimer's disease and peroxisome proliferator-activated receptor that is associated with inflammation, diabetes, and obesity. We also study drug targets involved in a variety of pathways (e.g. sphingosine kinases, ERKs, etc) to provide insight into drug discovery. Finally, we use bioinformatic tools to understand pathway relationships of proteins and assess motif presences in genomes.

Phone:  540-231-9231
Email:  ambrown7@vt.edu

Research Groups: 
Bevan & Brown Lab

Dr. Chung's research interests include numerical methods and software for computing solutions to inverse problems that arise in imaging applications.

Phone: 540-231-6531
Email: jmchung@vt.edu

Research and Affiliations: 
Dr. Chung's Homepage

Dr. Chung's research interests concern various forms of inverse problems. Driven by their application, Dr. Chung develops and analyzes efficient numerical methods for inverse problems. Applications of interest are, but not limited to, systems biology, medical and geophysical imaging, and dynamical systems.

Phone: 540-231-3466
Email: mcchung@vt.edu

Research and Affiliations: 
Dr. Chung's Homepage

Teaching statement of Dr. de Sturler:

The Rime of the Ancient Professor

(EdS, after Colridge's The Rime of the Ancient Mariner)

O teach me, teach me, learned man!
The student dothe implore. 
Tell me, quoth she, of PRD
And ODE much more.

Forthwith this frame of mine was wrenched
With a woeful agony,
Which forced me to begin my class; 
And then it left me free.

Since then, each week the selfsame hour, 
That agony returns:
And till I have my lecture told, 
This heart within me burns.

Three times a week I go to class; 
I have strange power of speech;
That moment that her face I see, 
I know the student must hear me:
To her my class I teach.

Phone: 540-231-5279
Email: sturler@vt.edu  

Research and Affiliations: 
Dr. de Sturler's Homepage
Synergistic Environments for Experimental Computing
Materials Computation Center
(University of Illinois at Urbana-Champaign)

Associate Professor, Statistics
Visiting Collaborator, Biocomplexity Institute

Research Interests:

  • Interface between design of experiments and machine learning
  • Model and analysis of high-dimensional data
  • Covariance matrix estimation and its applications
  • Statistical methods to Nanotechnology
  • Statistical modeling with applications in financial services

Professor, Mathematics
Program Leader, Computational Modeling and Data Analytics
Associate Director, Virginia Tech's Smart Infrastructure Laboratory

Dr. Embree's research interests includeinverse eigenvalue problems in vibration, spectral theory for non-self-adjoint operators, and algorithms for large-scale linear algebra.

Professor Faltin's research interests include:
  • Process monitoring and control
  • Manufacturing and service process improvement
  • Risk management



Phone: 540-231-2252
Email: ffaltin@vt.edu

Professor, Statistics

Dr. Gramacy's research interests include Bayesian modeling methodology, statistical computing, Monte Carlo inference, nonparametric regression, sequential design, and optimization under uncertainty. 

Phone: 540-231-5657
Email:  rbg@vt.edu

Research and Affiliations: 
Dr. Gramacy's Homepage

Dr. Gugercin's research lies in the area of model reduction, the primary goal of which is to replace large-scale dynamical systems with lower dimensional dynamical systems having as near as possible the same input/output response characteristics as the original. 

In contexts where the input/output characteristics are primary, the resulting reduced model can then be used to replace the original model, potentially as a far more efficient component within a larger simulation.

This research area is highly interdisciplinary in character and has a large overlap with other areas of mathematics and scientific computing, such as numerical analysis, systems and control theory, and optimization. It has found immediate application in diverse areas of the physical sciences and engineering including signal propagation and interference in electric circuits; (PDE) constrained optimization; uncertainty quantification and inverse problems.  Dr. Gugercin has focussed on both theoretical and computational aspects of model reduction as well as their application in real-world problems.

However, the methods and theory he develops are not specific to a particular application; rather they apply to a wide range of problems.

Phone: 540-231-6549
Email: gugercin@math.vt.edu  

Research and Affiliations: 
Dr. Gugercin's Homepage  

Phone: 540-231-6536
Email: phaskell@math.vt.edu

Research and Affiliations: 
Dr. Haskell's Homepage

Assistant Professor, Mathematics

Dr. Hewett’s research interests include:

  • Computational inverse problems and data assimilation at extreme compute and data scales
  • Deep learning as a physically constrained inverse problem
  • Applications in geoscience, atmospheric and space physics, medical imaging, photography, and computer vision
  • Software engineering for Computational Science & Engineering

Phone: 540-231-6171
Email: rhewett@vt.edu

Research and Affiliations: 
Dr. Hewett's Homepage

Associate Professor, Statistics

Dr. House's research interests include:

  • Bayesian statistical modeling with an emphasis in model averaging, kernel regression, and Bayes linear
  • Uncertainty analysis of computer models/experiments
  • Data mining coupled with data visualization that promotes human-data interaction and education in Statistics
  • Applications in proteomics, bioinformatics, cosmology, climatology, and hydrology

Phone: 540-231-2256
Email: lhouse@vt.edu

Research and Affiliations: 
Dr. House's Homepage
Discovery Analytics Center

Assistant Professor, Statistics

Dr Johnson is a quantitative ecologist working at the intersection of statistics, mathematics, and biology. At a broad level, her research focuses on understanding how differences between individuals in a population result from external heterogeneity and stochasticity, and how this variability influences population level patterns. She address these questions primarily in the context of infectious disease epidemiology, as well as in behavioral and population ecology. Her approach is to use theoretical models to understand how systems behave generally, while simultaneously seeking to confront and validate models with data and make predictions. Thus, a significant portion of her research focuses on methods for statistical — particularly Bayesian — inference and validation for mechanistic mathematical models of biological and ecological systems. Specific application areas have included the transmission of vector-borne diseases and population dynamics of animals.

Phone: 540-231-5657
Email: lrjohn@vt.edu

Associate Professor, Statistics

Dr. Kim's research interests focus on developing semi/nonparametric statistical methods and theory using regression splines or Gaussian process to address issues in several areas (epidemiology, medicine, genomics, proteomics, and system biology) for high and low dimensional analysis. Both Frequentist and Bayesian methods have been developed.

Phone: 540-231-5366
Email: inyoungk@vt.edu

Research and Affiliations: 
Dr. Kim's Homepage

Associate Professor, Statistics

Dr. Leman's core research interests include Bayesian statistics on both a theoretical and inferential level, MCMC mixing theory, Data Augmentation for efficient simulation, large scale stochastic modeling, molecular evolution, and coalescence processes. Additionally, he has a strong interest visualization techniques, which involve Human-Computer-Interaction. More specifically, given visual displays, Dr. Leman is interested in how users can inject feedback, so that resulting displays are a merger between the data, visualization model, and the user's cognitive insights. Such methods prove to be exceedingly useful in exploring relevant information in very high-dimensional spaces.

Phone: 540-231-5441
Email: leman@vt.edu

Research and Affiliations: 
Dr. Leman's Homepage

Collegiate Faculty, Statistics

Dr. Lucero is interested in both computational and statistical methodology applied in a variety of scientific fields.  He is extremely passionate about teaching the next generation of computational/data scientists.

His interests involve the following general areas:

  • Inverse Problems
  • Uncertainty Quantification
  • Statistical Learning
  • Experimental Design
  • Interdisciplinary Applications

Phone: 540-231-5657
Email: chlucero@vt.edu

Assistant Professor in Mathematics

Dr. Martin's research focuses on computational science related to the built and natural environment, particularly subsurface imaging and source detection. This includes inverse problems, imaging science, signal processing, and augmenting computational science with data science techniques. She often works with large, streaming data sets, and has extensive experience with data recorded by fiber optic distributed acoustic sensing networks.

Phone: 540-231-5960
Email: eileenmartin@vt.edu

Research Groups: 
Dr. Martin's Homepage

Professor, Mathematics

Dr. Matthews’ research focuses on applications of algebraic geometry and combinatorics to problems in communications and data storage, especially coding theory and cryptography.

Professor, Statistics
Associate  of Strategic Initiatives, College of Science

Dr. Morgan's Research Interests include:

  • Experimental design
  • Combinatorics
  • Discrete optimization

Phone: 540-231-6738
Email: jpmorgan@vt.edu

Research Groups: 
The College of Science

Dr. North's research seeks to enable people to interactively visualize and explore big data for discovering new insights, by establishing usable, effective, and scientifically grounded methods for visual interaction. His current research themes focus on creating powerful interactions for computational analytics that respond to human cognitive sense making activity, and exploiting large high-resolution displays to create rich embodied-interactive spaces.

Dr. Piilonen leads an internationally known research program in high-energy particle physics that focuses on charge-parity symmetry breaking in B meson decay. He is a leading member of the Belle collaborations at the KEK National Laboratory in Japan, and his work was cited as the experimental verification of the theoretical predictions honored with the Nobel Prize in Physics in 2008.

Phone: 540-231-3356
Email: piilonen@vt.edu

Research Groups: 
Dr. Piilonen's Homepage

Dr. Pleimling's research interests include:

  • Out-of-equilibrium dynamical behavior of complex systems: aging phenomena and dynamical scaling
  • Critical phenomena in confined geometries
  • Microcanonical analysis of small systems

Thomas L. Phillips Professor of Engineering, Computer Science
Director, Discovery Analytics Center

Dr. Ramakrishnan's research interests include mining scientific datasets in domains such as systems biology, neuroscience, sustainability, and intelligence analysis. His work has been featured in the NIH outreach publication Biomedical Computation Review, the National Science Foundation’s Discoveries series, Wall Street JournalNewsweekSmithsonian Magazine,Popular ScienceSlate magazine, and ACM Technews.

Professor and Department Head, Computer Science
Associate Director, Center for High-End Computing Systems

Dr. Ribbens' primary research interests are in parallel computation, high-end computing and computational science. Current topics of interest include distributed shared memory systems, concurrency bug detection and recovery, algorithms and tools for improving utilization and throughput on parallel systems via dynamically re-sizable (malleable) parallel computations, and algorithms and tools for improving the performance of large-scale computational ensemble computations and sparse linear-algebra kernels. Other topics of recent and possible future interest include numerical linear algebra and mathematical software for PDEs, grid computing (including scheduling, load balancing, code composition frameworks, fault tolerance, and resource-aware issues), and problem solving environments.

Phone: 540-231-6262
Email: ribbens@vt.edu

Research Groups: 
Dr. Ribbens' Homepage
Center for High-End Computing Systems

Assistant Professor, Statistics

Dr. Sengupta’s research interests are primarily in statistical methodology for network data, bootstrap and related resampling methods, big data, and computational statistics.

He is also interested in statistical applications in wide-ranging problems in science and industry.

Phone: 540-231-5657
Email: sengupta@vt.edu

Research Groups: 
Dr. Sengupta's Homepage

Professor, Statistics

Dr. Smith's research interests include: 

  • Multivariate analysis
  • Multivariate graphics
  • Biological sampling and modeling
  • Ecotoxicology
  • Data analytics
  • Visualization

Phone: 540-231-4801
Email: epsmith@vt.edu

Professor, Mathematics

Dr. Warburton is a Professor of Mathematics and he holds the John K. Costain Faculty Chair in the College of Science at VT. He is the Graduate Program Chair in Mathematics and is also affiliated with the CMDA program, teaching the CMDA 3634 parallel computing for undergraduates course.

Dr. Warburton's research interests include the development of highly parallel numerical algorithms in particular for graphics processing units. He has developed novel high-order discontinuous Galerkin methods and explored their use in high fidelity physical modeling of acoustics, elastodynamics, electromagnetics, fluid dynamics, and plasma physics.

Phone: 540-231-8274
Email: tcew@vt.edu

Research Groups: 
Dr. Warburton's Homepage

Instructor, Mathematics

Dr. Wilson's focus is teaching both CMDA and Mathematics classes. He teaches the math portion of CMDA 2005 and CMDA 2006, as well as CMDA 3605 and CMDA 3606. His research area is large scale linear algebra.

Phone: 540-231-8113
Email: jasonwil@vt.edu

Associate Professor, Mathematics

Dr. Zietsman's current research interests involve the development and analysis of numerical methods for solving optimal control problems where the dynamics are described by partial differential equations; for example, fundamental fluid flows. This includes applications such as the design, optimization and control of energy efficient buildings. Commercial buildings are responsible for 40% of the energy consumption and greenhouse gas emissions worldwide and significantly exceed those of all transportation combined. Reducing energy consumption of commercial buildings can have a tremendous impact on energy cost and greenhouse gas emission.

Phone: 540-231-2767
Email: lzietsma@vt.edu

Research Groups: 
Dr. Zietsman's Homepage

Collegiate Assistant Professor Ufferman teaches classes in both Computational Modeling and Data Analytics and Discrete Mathematics. He has worked on developing our undergraduate cryptography sequence and directed related undergraduate research projects. As a member of the orientation and lower-division advising teams, he works to help first-year Math majors with the transition to the university environment.

Email: ericu1@vt.edu
Phone: 540-231-3982