Who We Are

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


Nora Sullivan

Nora Dragovic

Program Manager & Advisor,

Academy of Integrated Science

Email: nora84@vt.edu

Phone: 540-231-8131



Carrie Hopkins

Academic Advisor,

Academy of Integrated Science

Email: carrieh7@vt.edu

Phone: 540-231-2442


Core and Affiliated Faculty

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

Contact: 

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.

Contact: 

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.

Contact: 

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

Contact: 

Phone: (540) 231-5638

Email: xdeng@vt.edu

Professor, Mathmatics

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, Statistics

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

Contact: 

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. 

Contact: 

Phone: (540) 231-6549

Email: gugercin@math.vt.edu   

Research and Affiliations: 

Dr. Gugercin's Homepage  

Contact: 

Phone: (540) 231-6536

Email: phaskell@math.vt.edu    

Research and Affiliations: 

Dr. Haskell'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

Contact: 

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.

Contact: 

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. 

Contact: 

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.

Contact: 

Phone: (540) 231-5441

Email: leman@vt.edu 

Research and Affiliations: 

Dr. Leman's Homepage

 

Professor, Statistics

Associate Dean of Strategic Initiatives, College of Science

Dr. Morgan's Research Interests include:

  • Experimental design
  • Combinatorics
  • Discrete optimization

Contact: 

Phone: (540) 231-6738

Email: jpmorgan@vt.edu

Research and Affiliations: 

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.

Contact: 

Phone: (540) 231-2458

Email: north@vt.edu

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.

Contact: 

Phone: (540) 231-3356

Email: piilonen@vt.edu

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

Contact: 

Phone: (540) 231-6073

Email: pleim@vt.edu

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.

Contact: 

Phone: (571) 858-3331

Email: naren@cs.vt.edu

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.

Contact: 

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.

Contact: 

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

Contact: 

Phone: (540) 231-4801

Email: epsmith@vt.edu

   

Associate Professor, Mathematics

Dr. Zeitsman'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.

Contact: 

Phone: (540) 231-2767

Email: lzeitsma@vt.edu

   

Research Groups: 

Dr. Zeitsman's Homepage