Applied Mathematics & Statistics, and Scientific Computation

AMSC Faculty Research Interests

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
Name & Contact Research Interests
A
Ashok K. Agrawala
agrawala at cs.umd.edu
Design and evaluation of systems and networks.
David Akin
dakin at ssl.umd.edu
Space Systems, Space Robotics, Space Human Factors, Extravehicular Activity/Space Suit Design.
Frank B. Alt
falt at rhsmith.umd.edu
Statistical quality control, applied multivariate analysis, and forecasting with a particular interest and expertise in multivariate process control.
Stuart S. Antman
ssa at math.umd.edu
Professor Antman studies a variety of dynamical problems for rods, shells, and three-dimensional solid bodies. The bodies are composed of nonlinearly elastic, viscoelastic, plastic, viscoplastic, or magnetoelastic materials. In each case, properly invariant, geometrically exact theories encompassing general nonlinear constitutive equations are used. In some cases, the solids interact with fluids or electromagnetic fields. The goals of these studies are to discover new nonlinear effects, determine thresholds in constitutive equations separating qualitatively different responses, treat control problems
involving "smart" materials, examine important kinds of instabilities, contribute to the theory of shocks and dissipative mechanisms in solids,
and develop new methods of nonlinear analysis and of effective computation for problems of solid mechanics.
Mark A. Austin
austin at isr.umd.edu
Systems engineering and integration- How do we build systems engineering tools that can take advantage of semantic web technologies? Systems engineering for sensor-based supply chains. Human-computer interfaces for system-level engineering design. Formal models for validation/verification of networked engineering systems. Computer-aided design of bridge and building structures. Earthquake engineering and structural dynamics.
Bilal Ayyub                       ba at umd.edu Dr. Ayyub’s main research interests are risk, uncertainty and decision analysis, and systems engineering applied to civil, infrastructure, energy, defense and maritime fields.
Shapour Azarm
azarm at umd.edu
Evolutionary/classical multi-objective and multi-disciplinary design optimization. Approximation of computationally intensive simulations. Decision maker's (or customer's) preference capturing for product design selection. Robust design optimization and selection, with applications for single product and product line design. Integration of marketing and engineering design.
B
Balan Balachandran         balab at umd.edu
Radu V. Balan                  rvbalan at cscamm.umd.edu Applied harmonic analysis, signal processing, machine learning, modeling.
Michael O. Ball
mball at isr.umd.edu
Dr. Ball's research interests are in network optimization and integer programming particularly as applied to problems in transportation systems and supply chain management.
John S. Baras
baras at isr.umd.edu
Dr. Baras' research interests include scaleable multicast security; integrated management of hybrid communication networks; modeling and performance evaluation of large broadband hybrid networks; fast internet over heterogeneous (wireless-wireline) networks; manufacturing process selection for electromechanical products; intelligent control; wavelets; robust speaker identification; low complexity, high fidelity, low rate speech coding; image processing and understanding; learning clustering algorithms and classification; distributed control (or decision) systems; stochastic dynamic model building; stochastic control and scheduling; real-time sequential detection and estimation; computer-aided control systems design; queuing systems; quantum communications; nonlinear systems; and radar systems modeling and performance evaluation and distributed parameter systems.
Alexander Barg
abarg at umd.edu
Combinatorics, Geometry, Coding Theory, Information Theory, Cryptography, Applied problems in Communications, Storage, and Data Protection
Sean Barnes                   sbarnes at rhsmith.umd.edu Dr. Barnes' research interests are modeling the transmission of infectious diseases, healthcare and sports analytics, agent-based modeling, simulation, data visualization, and machine learning.
Jacob Bedrossian             jbedross@umd.edu My research is focused on the mathematical analysis of PDEs arising in fluid mechanics and plasma physics. Recently, most of my work has focused on understanding mising and nonlinear stability in fluid mechanics at high Reynolds number and Landau damping-related effects in kinetic theory in the collisionless limit with a specific interest to problems relevant to plasma physics.
John J. Benedetto
jjb at math.umd.edu
Harmonic analysis and applications
William Bentley           bentley@umd.edu        Recent interests are on deciphering and manipulating signal transduction pathways, including those of bacterial communication networks, for altering cell phenotype. To enable discovery, his lab develops new strategies for opening ‘communication’ between devices and biological systems by the creation and facile assembly of biologically functional interfaces. These concepts are emerging as a field of ‘biofabrication’ that exploits biological components and processes for assembly.
Peter S. Bernard
bernard at eng.umd.edu
Professor Bernard's primary research interests lies in gridfree methods for turbulent flow simulation, including heat and mass transfer and natural convection. Lagrangian analysis of turbulent transport.
Gilmer L. Blankenship
gilmer at umd.edu
Robotics, nonlinear dynamics, stochastic systems, software systems for real-time control
Dieter R. Brill
brill at physics.umd.edu
Black Hole Physics, Cosmology, (2+1)-dimensional model theories
Hugh A. Bruck
bruck at umd.edu
Processing, thermomechanical characterization, and computational design of multifunctional and functionally graded materials, energetic materials, nanocomposite materials, smart structures, and thin films; experimental methods for microscale and nanoscale materials
characterization.
Daniel Butts                     dab at umd.edu Systems and computational neuroscience; visual and auditory processing; application of statistical and machine learning approaches to interpret neurophysiological data with a focus on large-scale recordings.
C
Richard V. Calabrese
rvc at umd.edu
Dr. Calabrese's research interests are in turbulent mixing and multiphase flow, with emphasis on drop dispersion and coalescence, prediction and measurement of particle size distribution and prediction and measurement of velocity fields in stirred vessels, high shear mixers and other process equipment.

Marie Cameron     cameron at math.umd.edu

Scientific computing, development of numerical and graph algorithms, methods for the study of rare events and transition paths in stochastic systems, and applications to natural sciences, in particular to chemical physics.
James A. Carton
carton at atmos.umd.edu
Ocean dynamics and the role the ocean plays in climate variability. Current interests include tropical climate variability; exchange processes between the North Atlantic and Arctic (and their relationships to sea ice loss); the changing geochemistry of the oceans; and techniques for reconstructing historical variability of ocean climate.

Sandra Cerrai           cerrai at math.umd.edu

Probability theory, Stochastic partial differential equations
Rama Chellappa
rama at umiacs.umd.edu
Signal and image processing, computer vision, pattern recognition, multi-dimension stochastic processes, statistical inference, computer vision and image analysis, AI in computer vision, neural networks for computer vision.
Andrew Childs                 amchilds at umd.edu

Hector Corrado Brava hcorrada at umiacs.umd.edu

Our research focuses on efficient and effective interactive analysis of high-throughput genomic data. We develop new methods and tools from multiple areas in the computational and statistical sciences: basic bioinformatics/biostatistics, statistical and machine learning, data visualization and management, and numerical optimization. Applications include cancer epigenetics, metagenomics, pre-processing of measurements from high-throughput assays and disease risk models that integrate high-throughput genomic and other data.
Peter J. Coughlin
coughlin at econ.umd.edu
Dr. Coughlin's research interests are in the areas of social choice, voting theory and applied game theory.

Peter Cramton       cramon at umd.edu

Dr. Cramton conducts research on auctioning many related items, and applies that research world-wide to major auctions of radio spectrum, electricity, financial securities, rough diamonds, pollution emissions, timber, and other products.

Michael Cummings mcummin1 at umd.edu

Molecular evolution, bioinformatics, computational biology, machine learning, genotype-phenotype relationships, GPU-computing, high performance computing.

Wojciech Czaja                 wojtek at math.umd.edu

Applied and theoretical harmonic analysis; signal and image processing; machine learning.
D
Larry S. Davis
lsd at umiacs.umd.edu
Computer Vision, Homeland security, visual surveillance
Anil Deane                         deane at ipst.umd.edu Dr. Deane's research is in the area of computational fluid dynamics and parallel computing, with funded projects in space physics, microgravity fluid physics and high performance computing. Over time he has worked on large-scale simulations of thermal convection, wake flows, compressible turbulence, and magnetohydrodynamics. The numerical techniques used for these simulations include spectral methods, spectral-element methods, finite volume schemes for compressible flows, and shock-capturing methods (particularly flux-corrected transport).
William D. Dorland
bdorland at umd.edu

Development of kinetic (phase space) algorithms for high performance computing, with an emphasis on Eulerian schemes and closure theory Direct numerical simulation of collisionless, magnetized plasma turbulence for first-principles simulation of: Turbulent transport in magnetic confinement fusion devices Turbulent heating and particle acceleration in astrophysical plasmas

Development of lightweight, portable, high-performance components for practical high performance parallel computing

Alex J. Dragt
dragt at physics.umd.edu
Nonlinear Dynamics, Lie Algeba, Accelerator Physics, Quantum Computing
Ralph Dubayah
rdubayah at glue.umd.edu
Ecosystem characterization for carbon modeling, habitat and biodiversity studies, land surface energy and water balance modeling, spatial analysis and remote sensing science
James H. Duncan              duncan at umd.edu Experiemental research in water surface waves including wave breaking, wave impact on structures, droplet and bubble generation, and solitary gravity capillary waves.
Ramani Duraiswami
ramani at umiacs.umd.edu

Audio and Computational Acoustics: Acoustics for perceptual reality, microphone arrays, auditory user interfaces, underwater acoustics. Scientific Computation: Fast multipole methods, computational statistics and learning methods, data fitting and modeling, boundary element methods

Computer Vision: Vision aware audio, tracking, pose

E
Theodore L. Einstein
einstein at umd.edu
Physics of surfaces and complex interfaces, Properties of vicinal surfaces, Statistical mechanics of lower dimensions.
Howard C. Elman
elman at cs.umd.edu
My research concerns various topics in Numerical Analysis, including numerical linear algebra, computational methods for partial differential equations, computational fluid dynamics, uncertainty quantification, and parallel computation.
Anthony Ephremides
tony at eng.umd.edu
Research interests include all aspects of Communications Systems (Information Theory, Communication Theory, Multi-user Systems, Communication Networks, Satellite Systems) with focus on Energy Efficiency and Cross-Layer Approaches to Design. He is also interested in Systems Theory, Stochastic Systems, Optimization, Signal Processing, Wireless Communications
Michael Evans                   mnevans at umd.edu High resolution multiproxy paleoclimatology of the late Holocene, with special emphasis on tropical processes, hydrometeorological variations, and global climate change
F
William F. Fagan
bfagan at umd.edu
I use analytical and computational approaches to understand aspects of population dynamics and species interactions. I focus on problems in spatial ecology using systems of PDEs, integrodifference equations, agent-based modeling, and network modeling. I also study aspects of extinction risk and parameter estimation from noisy time series using stochastic population models. Some of my models are 'pure theory' in nature whereas others are tightly tied to data from particular field systems (e.g., Mount St. Helens).
Patrick M. Fitzpatrick
pmf at math.umd.edu
Topological Methods in Nonlinear Operator Theory
Giovanni Forni                   gforni at math.umd.edu Dynamical systems and smooth ergodic theory of zero entropy systems, Renormalization methods in dynamical systems, KAM theory, Teichmueller dynamics, Homogeneous Dynamics and Number Theory, Billiards in Polygons and related systems, Unipotent Flows (horocycle flows, nilflows) and their Time-Changes.
Michael Fox-Rabinovitz
foxrab at essic.umd.edu
Development of variable-resolution stretched-grid (SG)-GCMs and SG-DASs (data assimilation systems) for regional and subregional climate and climate change and other studies and applications.

Studies of anomalous regional climate events including the major monsoonal circulations (like NAMS), and the extreme summer precipitation events (like the U.S. summer droughts and floods), with the SG-GCM and SG-DAS.

Collaborative studies on atmospheric chemistry transport experiments.

Initiation of and participation in the international SGMIP (Stretched-Grid Model Intercomparison Project)

Collaborative interdisciplinary studies on developing and implementation of fast and accurate neural network approximations for model physics.

Numerical approximations and filters.

Mark I. Freidlin
mif at athena.umd.edu
Asymptotic Problems Stochastic Processes and PDEs
Michael C. Fu
mfu at isr.umd.edu
Simulation modeling and analysis, production/inventory control, applied probability, and queueing theory; stochastic derivative estimation, simulation optimization of discrete-event systems, Markov decision processes; with application to supply chain management and financial engineering.
G
Steven A. Gabriel
sgabriel at umd.edu
Development of models and algorithms in Operations research, optimization, and equilibrium modeling as applied to problems in infrastructure such as
1. Nash-Cournot games in natural gas and electricity markets
2. Optimal determination of retail electricity contracts with stochastic load and prices
3. Bilevel planning problems in energy with discrete upper-level variables
4. Multiobjective optimization as applied to waste management, telecommunications networks, and land development
5. Stochastic market equilibrium problems
William Gasarch
gasarch at cs.umd.edu
Communication Complexity, Circuits, Games, Logic.
Sylvester J. Gates
gatess at umd.edu
My career interest in the mathematical and theoretical physics of supersymmetric particles, fields and strings began with my Ph.D. thesis, the first on the topic of SUSY at MIT in 1977, and has continued throughout my career. In recent times my focussed interests have been upon two classes of problems: (a) the foundations of the symmetries of superstring/M-theory and (b) 4D, N = 1 supersymmetry in the context of hadron phenomenology and effective actions. More generally, however, I do work in a broad range of investigation involving supersymmetrical systems.

Keywords:
Superstring Theory, M-Theory, Supersymmetrical Systems

Michelle Girvan           girvan at umd.edu My research focuses the theory of complex networks as well as applications to biological systems. Much of the theoretical portion of my work involves studies of community structure (e.g. modularity) in complex networks – how it arises, different ways to quantify it, algorithms to detect it, etc. In terms of applying abstract concepts from network theory to experimental systems, I am broadly interested in high-throughput biological networks, and have recently been focused on gene interaction networks. In particular, my collaborators and I have been studying structural and dynamical features of cancer in experimentally-derived gene interaction networks. In an effort to connect empirical results back to theory, we are investigating the utility of Boolean models of genetic control for understanding the diverse patterns of gene expression observed in cancer cells.
Harland M. Glaz
hmg at math.umd.edu
Numerical Analysis
Bruce L. Golden
bgolden at rhsmith.umd.edu
Some of my interests are network optimization, genetic algorithms, evolutionary computation, heuristic search, applied operations research, operations research/operations management in healthcare, logistics & distribution.
William M. Goldman
wmg at math.umd.edu
I am interested in the deformation theory of geometric structures on manifolds. Such structures are modeled on geometris on homogeneous spaces of Lie groups. They include hyperbolic geometry, projective geometry, inversive geometry, constant curvature Lorentzian geometry and many others. The study closely relates to discrete subgroups of Lie groups, gauge theory, low-dimensional topology and mathematical physics. Of particular interest is the action of the topological symmetry group (the mapping class group) on the deformation space (generalizing Teichmueller space), which opens up many questions in dynamical systems.

The Experimental Geometry Lab provides a community of mathematicians working on examples of these structures using technology. In particular we are interested in visualization and computation for geometric structures, discrete group actions, and dynamical systems on moduli spaces. Participants in the lab have included senior researchers, postdocs, graduate students, undergraduate students and high school students.

Keywords:
manifold, geometry, homogeneous space, Lie group, symmetry, geometric structure, mapping class group, uniformization, moduli space, dyanmical system

Oscar W. Greenberg
owgreen at physics.umd.edu
I am interested in the relation of discrete symmetries, locality of various types and Lorentz invariance. I am presently studying the spacetime dependence of the relative spin-spin correlation function connected with tests of the Bell inequalities. More generally, I am interested in quantum information and related issues.
Manoussos Grillakis
mng at math.umd.edu
Nonlinear waves and stability, Nonlinear partial differential equations, Harmonic Analysis
Nail A. Gumerov
gumerov at umiacs.umd.edu
My research interests are broad and include many interdisciplinary areas where mathematical modeling and efficient ways of solution of mathematical problems are crucial.

Keywords:
Acoustics, Computational Methods, Mathematical Methods, Inverse Problems,Physichochemical Hydrodynamics, Multiphase Flows, Classical Hydrodynamics and Aeromechanics, Electromagnetic Waves, Computer Vision

H
Nicholas J. Hadley
hadley at umd.edu
My interests are in experimental particle physics. Appropriate topics for AMSC students include the applications of computing to large data sets using the grid, and simulating and reconstructing data using pattern recognition and other algorithms.
Jin-Oh Hahn                    jhahn12 at umd.edu System dynamics and control, system identification, condition monitoring and fault diagnostics, multi-sensor fusion and signal processing, bio-systems and healthcare, automotive control systems, energy systems
Adil B Hassam
hassam at umd.edu
Controlled Thermonuclear Fusion, Solar-Terrestrial Plasma Physics, Industrial Plasmas.

Keywords:
Theoretical Plasma Physics

Xin He                           xinhe at umd.edu Longitudinal data analysis, time-to-event data analysis, nonparametric and semiparametric methods, as well as applications in epidemiology, environmental health, and biomedical studies.
Jeffrey Herrmann
jwh2 at isr.umd.edu

Developing risk-based methods for planning and optimizing unmanned sysytems operations.

Keywords: Operations Research, Decision Making, Risk Management 

Timothy K. Horiuchi
timmer at isr.umd.edu
Bat Echolocation, Computational Neuroscience, Learning Systems, Neuromorphic VLSI Design,Constrained Optimization Circuits, Mobile Robotics, Neural Recording and Spike-Sorting Techniques and Tools
Bei-Lok Hu
hub at physics.umd.edu
Quantum Field Theory in Curved Spacetime, Stochastic Semiclassical Gravity, Early Universe Quantum Processes, Nonequilibrium Quantum Field Theory. Fluctuation Phenomena. Foundational Issues of Quantum Mechanics, Relevance to Quantum Computing. Theoretical Aspects of Quantum and Atom Optics.
Brian R. Hunt
bhunt at ipst.umd.edu
Weather Forecasting and State Estimation for Spatiotemporal Chaos. Prevalence, Projection, and Dimension. Fractals and Dimension in Dynamical Systems. Optimal Orbits and Invariant Measures of Chaotic Systems. Dynamics on Networks. Dynamics near Invariant Manifolds: Intermingled Basins, Bubbling, and Synchronization. Bifurcations and Periodic Windows. Other Dynamical Systems Papers. Computational Genomics. Keywords:
Chaotic Systems, Applied Dynamics
J
Pierre-Emmanuel Jabin   pjabin at cscamm.umd.edu Advection-Transport equations with applications to compressible Fluid Mechanics, Multi-agent and many particles systems. Mathematical Modeling in Biology and Ecology, Kinetic and Hyperbolic problems.
David Jacobs               dwj@umd.edu               Object recognition in images, computational and psychological study of perceptual organization
I
Kayo Ide
ide at umd.edu
Dr. Ide's research interests concern dynamics of atmosphere and oceans from interdisciplinary perspective, in particular: data assimilation as scientific monitoring and prediction, observing system design, and study of transport and mixing from perspectives of dynamical and control systems.
K
Eugenia E. Kalnay
ekalnay at atmos.umd.edu
Predictability and ensemble forecasting, numerical weather prediction, data assimilation, coupled ocean-atmosphere modeling and climate change.
Jonathan Katz
jkatz at cs.umd.edu
I work on problems in theoretical computer science, mainly in the area of cryptography. I am interested in problems both of a combinatorial and an algebraic/number-theoretic nature. If you are interested in research in this area, please consult the list of publications on my web page or send me an email.
Benjamin Kedem
bnk at math.umd.edu
I have done work in time series analysis, space-time statistical problems, and combination of information from several sources.
Rami A. Kishek
ramiak at umd.edu
Kishnek's research is in applied electromagnetics (beams, plasmas, microwaves) and the nonlinear dynamics of many-body systems, with specific interest in space charge effects, computation, and multipactor. Broad applications include high-intensity particle accelerators and space-based communication systems. Nearly 25 years experience as a researcher and educator.
P.S. Krishnaprasad
krishna at isr.umd.edu

Krishnaprasad's interests lie in the broad areas of geometric control theory, filtering and signal processing theory, robotics, acoustics, and biologically-inspired approaches to control, sensing and computation. He has made contributions to system identification, geometric mechanics, actuation based on smart materials, and control of collectives. His current work is focused on pursuit and cohesion in nature and in engineered systems.

Key words: geometic methods, collective behavior, Lie groups, stability and control, pursuit phenomena, bio-inspiration, statistical physics, evolutionary games.

David W. Kueker             dwk@math.umd.edu        Mathematical logic - model theory
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Richard J. La             hyongla at umd.edu Richard J. La's research interest are i) mathematical analysis of communication networks, ii) design and evaluation of resource allocation algorithms for communication networks, and iii) application of game theory and mechanism design. In particular, his past research activities focused on congestion control in the Internet, wireless scheduling, mobile ad-hoc network routing, disruption tolerant networks, network pricing, and dynamic spectrum trading.
Johan Larsson                 jola at umd.edu Computational turbulence, grid-adaptation for chaotic PDEs, and uncertainty quantification applied to problems in fluid mechanics.
Mei-Ling Ting Lee                 mltlee@umd.edu Analysis of genomic data; analysis of time-to-event data; rank tests for clustered data; statistical applications in environmental and occupational health studies, epidemiology studies, microbiology and pharmaco epidemiology; applied probability models; multivariate distributions
Sung W. Lee
lee at umd.edu
Structural mechanics, finite element analysis, and composite structure
Ved Lekic                         ved at umd.edu
Shreevardhan Lele
slele at rhsmith.umd.edu
Dr. Lele's research centers on data mining and managerial decision-making under uncertainty. He has also conducted research in the fields of real options, quality control, and simulation
C. David Levermore
lvrmr at math.umd.edu
Much (but not all) of my research has revolved around the central theme of understanding how large-scale behaviors emerge from dynamics or structures on small-scales. This includes the classical question of statistical physics about the macroscpic desciption of systems of large numbers of particles given known microscopic physics. It also includes studies of semiclassical limits of nonlinear wave equations, convergence of numerical schemes, turbulence modeling, derivations of shallow water systems, derivations of fluid dynamical systems from kinetic theories, radiation transport through random media, and many other areas. These problems all fall into the what is now called the class of "multiscale" problems.

Keywords:
Multiscale problems, Boltzmann Equations, Nonlinear Wave Equations

Doron Levy
dlevy at math.umd.edu
Applications of math to biology and medical sciences, imaging, immunology, biology, nonlinear dynamics, numerical analysis.
K.J. Ray Liu
kjrliu at umd.edu
Dr. Liu is Director of Communications and Signal Processing Laboratories and leads the Maryland Signals and Information Group (SIG) with research contributions that encompass broad aspects of wireless communications and networking; multimedia communications and signal processing; information forensics and security; biomedical imaging and bioinformatics; and signal processing algorithms and architectures, in which he has published over 400 refereed papers, books, and book chapters.
Wolfgang Losert               wlosert@umd.edu The dynamical properties of Complex Systems at the convergence of physics, materials science, and biology.
David Lovell                     lovell at umd.edu  Surface and air transportation, systems engineering. Geometric design, optimization, and controls applied to civil infrastructure systems.
Viacheslav Lyubchich    lyubchich at umces.edu Time series analysis, forecasting, applied statistics, non-parametric inference, bootstrap, environmental modeling, and random networks.
M
Dilip B. Madan
dmadan at rhsmith.umd.edu
I am particularly fascinated by how mathematical analysis, economic theory, and statistical methodology may be employed to extract interesting information from financial market data. My particular area of expertise is Mathematical Finance with its wide array of theoretical, applied and innovative concerns that range from issues of formulating and testing our understanding of market price determination to the more detailed aspects of pricing particular claims, like the wide range of equity and fixed income derivatives now traded, and improving the quality of risk management through the development innovative financial products and better methods for processing financial information.

Keywords:
Mathematical Finance

Armand M. Makowski
armand at isr.umd.edu
Traffic characterization and modeling in communication networks (e.g., TCP modeling and web caching). Resource allocation issues in wireless networks. Queueing systems and asymptotic methods for performance evaluation in communication networks. Stochastic systems and adpative algorithms (e.g., swarm intelligence).

Keywords:
Communication networks

Shawn Mankad               smankad at rhsmith.umd.edu Studying the roles of networks and machine learning tools in primarily two areas: health care and the study of financial markets
Steven I. Marcus
marcus at isr.umd.edu
Dr. Marcus' research interests lie in the areas of control and systems engineering, analysis and control of stochastic systems, Markov decision processes, stochastic and adaptive control, learning, fault detection, and discrete event systems, with applications in manufacturing and communication networks.
Dionisios Margetis         diom at umd.edu Prof. Margetis's research interests lie broadly in mathematical modeling and applied analysis. In recent years, he has placed particular emphasis on: (i) modeling, analysis and simulation of solid materials across scales, especially derivation of macroscopic PDEs from discrete systems and germane issues of boundary conditions; (ii) quantum kinetic theory of ultra cold, dilute gases (``Bose-Einstein condensation''); (iii) PDE aspects of quantum information.
Isaak Mayergoyz
isaak at umd.edu
Power, Electromagnetic theory, Semiconductor device modeling.
Takemasa Miyoshi         miyoshi at atmos.umd.edu Fundamental problems about data assimilation theories and methods, with particular focus on ensemble-based data assimilation
Bahram Momen             bmomen at umd.edu Biostatistics and Environmental Science
Laurent G.J. Montesi montesi@umd.edu Our research group studies how the Earth and other planets are deforming and evolving over geological time scales. This research involves the development of Finite Element models of mantle flow, fault development and melt migration, with a fundamentally multidisciplinary approach. For example, we couple rheological evolution and deformation to produce localized shear zone, or couple thermodynamic and thermal models. Numerical challenge include multiphysics and multiscale processes, large deformation, adaptive mesh refinement, and the adoption of a Bayesian statistics framework for assimilation of many types of observations into our models.
David M. Mount
mount at cs.umd.edu
I am a member of the Algorithms and Theory Group at the University of Maryland. I do research on the design, analysis, and implementation of data structures and algorithms for geometric problems, particularly problems with applications in areas such as image processing, pattern recognition, information retrieval, and computer graphics.
N
Prakash Narayan
prakash at umd.edu
Multiuser information theory, Communication theory, Communication networks, Cryptography, Information theory and statistics.
Robert W. Newcomb
newcomb at umd.edu
Analog VLSI, biomedical engineering especially ear type systems and heart models), circuit and systems theory (especially semistate theory and multiport synthesis), microsystems, neural networks (hardware & biologically motivated), robotics.
Ricardo H. Nochetto
rhn at math.umd.edu
Free boundary problems and phase transitions: finite element methods, adaptivity, PDE issues
O
Douglas William Oard
oard at umd.edu
My research interests include cross-language information retrieval, speech-based information retrieval, and information filtering.
Kasso Okoudjou             okoudjou@umd.edu Harmonic analysis especially time-frequency and time-scale methods and their applications to signal analysis; Analysis and differential equations on fractals.
Dianne P. O'Leary
oleary at cs.umd.edu
My research has centered upon several themes, primarily related to computational linear algebra, scientific computing, and optimization. The work has involved a mixture of algorithm development and scientific applications, drawing upon tools in applied mathematics, numerical analysis, and computer science. These themes have led to applications in physics, biology, medicine, and engineering.

Keywords:
Numerical solution of ill-posed problems, image deblurring, Krylov sequence methods, optimization algorithms, information retrieval, and quantum computing.

Edward Ott
edott at umd.edu
Dynamics of large networks of coupled systems, Wave chaos, State estimation of large spatiotemporally chaotic systems.
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Derek Paley               dpaley at umd.edu Mobile sensor networks, Biocomplexity
Michael Pecht           pecht at umd.edu Professor Michael Pecht’s research focuses on prognostics and systems health management (PHM) using machine learning. PHM is an approach that is used to evaluate the reliability of a system in its actual life-cycle conditions, determine the initiation of failure, and mitigate system risks. Prognostics of a system can yield an advance warning of impending failure in a system and thereby help in maintenance and corrective actions.. The outputs of a prognostic assessment of a product are the failure risk, time to failure, remaining useful life, and a prognostic distance within which time specific maintenance and repair actions can be taken to extend the life of the product.. The U.S. Joint Strike Fighter (JSF) Program requires PHM.  NASA uses the Integrated Vehicle Health Management (IVHM) program for its fleet. Consumer electronics companies, including computer companies such as Dell, are investing a lot of money in prognostics research so that they can harness the benefits of PHM for reducing warranty costs and cutting product qualification time. The data-driven and fusion approaches stand among the three main approaches to implementing prognostics for a system (along with model-based). The data-driven prognostics methods use current and historical data to statistically and probabilistically derive decisions, estimates, and predictions about the health and reliability of products. Data-driven approaches are useful to monitor the health of large multivariate systems and are capable of intelligently detecting and assessing correlated trends in the system dynamics to estimate the current and future health of the system. Areas of interest for data-driven approaches include anomaly detection, fault identification, fault isolation and prediction of remaining useful life (prognostics). Machine learning is highly used in the data-driven approach since it incorporates statistical and probability theory in addition to data preprocessing, dimensionality reduction by compression and transformations, feature extraction, and cleaning (de-noising) of data. Fusion methods for prognostics offer the benefits of model-based and data-driven methods.
Stephen Penny                 pennysg at umd.edu Data Assimilation of the Ocean and Coupled Earth System, Mathematical foundations of data assimilation
Mihai Pop
mpop at umiacs.umd.edu
Genome assembly, Environmental Sequencing

Keywords:
Genomics
Computational Biology

Ingmar R. Prucha
prucha at econ.umd.edu
Dr. Prucha's research interests are in theoretical and Applied Econometrics. A focus of his current research is on the econometric analysis of spatial and social networks. His applied work focuses on the determinants of dynamic factor demand (including investment in physical and R&D capital) and productivity.
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Subramanian Raghavan
raghavan at umd.edu
Dr. Raghavan's research primarily focuses on three areas---network design (e.g., telecommunications, logistics), data mining, and auctions. The unifying feature to these various research areas is the network and combinatorial optimization techniques he applies to these problems.

Keywords:
Network Design, Combinatorial Auctions, Data Mining

James A. Reggia
reggia at cs.umd.edu
Our research group focuses on studying and understanding 1) the underlying principles of biological computation, and how these principles can be adopted or modified to extend contemporary computer science methods, and 2) automated causal reasoning, such as abductive inference and Bayesian/belief networks.

Keywords:
Biologically-inspired Computing, Causal Reasoning

Chris Reynolds       creynold@umd.edu Astrophysics of black holes (both stellar and supermassive), the physics of relativistic jets, and the properties and evolution of intracluster and intergalactic plasma
Amir Riaz                         ariaz at umd.edu
Jonathan M. Rosenberg
jmr at math.umd.edu
Topology and geometry, especially of manifolds and singular spaces, non-commutative topology, index theory, C*-algebras, Lie group representations, K-theory, applications to mathematical physics, especially string theory and other field theories

Keywords:
index theory, K-theory, non-commutative topology, C*-algebras, string theory

Estelle Russek-Cohen
erussek at umd.edu
Linear models and multiple inequality hypotheses. Discriminant Analysis. Statistical Issues in Microbiology.
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Robert Sanner
rmsanner at eng.umd.edu
Research interest include nonlinear control, spacecraft dynamics and control, aircraft dynamics and control.
Shihab Shamma
sas at isr.umd.edu
Dr. Shamma's research interests include biological aspects of speech analysis and neural signal processing.
Benjamin Shapiro
benshap at umd.edu
I am primarily intersted in research at the intersection of control theory and micro systems. We focus on model based control design with validation via experiments. Roughly speaking, we do 50% modeling, 30% control design, and 20% fabrication and experiments.
Tien-Mo Shih
tmshih at umd.edu
Developing a robust scheme to solve a set of nonlinear equations; Newton-Raphson method and its failure.
Frank Siewerdt         siewerdt@umd.edu Population-level changes in gene frequencies, genetic resemblance between individuals, selection theory, advanced statistical methods for prediction of breeding values, incorporation of novel techniques into breeding programs
Georgios Skoulakis gskoulak@rhsmith.umd.edu Asset pricing, portfolio choice, computational methods in economics, and financial econometrics
Eric V. Slud
evs at math.umd.edu
Survival data analysis, Census statistics, large-scale data problems with emphasis on cross-classified data, Stochastic processes. Keywords:
Mathematical statistics and probability
Paul J. Smith
pjs at math.umd.edu
Categorical data analysis. Robust and nonparametric statistical methods. Applications of statistics, particularly in the biomedical sciences.
Jiuzhou Song
songj88 at umd.edu
Dr. Song's current research interests are on bioinformatics, statistical genomics, biopathway analysis and gene regulatory network. Specifically, he works in novel computational methodologies for molecular biology and genetics, e.g., temporal gene expression analysis and biological information extraction from high throughput gene expression data.

Keywords:
Statistical genomics and bioinformatics

Aravind Srinivasan            srin at cs.umd.edu Prof. Srinivasan's research interests are in randomized algorithms, networking, social networks, and combinatorial optimization, as well as in the growing confluence of algorithms, networks, and randomness, in fields including the social web, machine learning, public health, biology, and energy.
Piotr Swistak
pswistak at umd.edu
Game theory, social choice theory, decision theory, methodology and philosophy of the social science.
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Eitan Tadmor
tadmor at umd.edu

Research is concerned with theory and computation of Partial Differential Equations with diverse applications to shock waves, kinetic transport, incompressible flows, image processing, and self-organized collective dynamics.In particular, research is focused on the development of high-resolution methods for nonlinear conservation laws, including those associated with the notions of central schemesentropy stabilityspectral viscosity methodsconstraint transport and edge detection; on transport models and their relation to kinetic theories, and on critical thresholds phenomena in such models; on multi-scale descriptions in image processing associated with the notion of hierarchical decompositions; and on modeling and analysis of collective (hydro-)dynamics with applications to flocking and opinion dynamics.

Andre L. Tits
andre at umd.edu
Dr. Tits' main research interests lie in various aspects of numerical optimization, optimization-based system design and robust control with emphasis on numerical methods. In addition to carrying out fundamental research work in these areas, researchers in Dr. Tits' group have developed several software packages. Especially popular is FSQP, a tandem of sophisticated software suites for nonlinear constrainted optimization, in use at over 1000 sites around the world.
Konstantina Trivisa
trivisa at math.umd.edu

Trivisa’s research lies on the interface between nonlinear partial differential equations and continuum physics and focuses on applications in fluid dynamics, multiphase flows, continuum mechanics, materials science and math biology. Her research is an interplay of mathematical modeling, analysis and simulations for the investigation of nonlinear systems governing physical models.

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Richard Valliant                 rvallian at umd.edu Survey sample design, calibration estimation, price index estimation, statistical software development, statistical education
Uzi Vishkin                 vishkin at umiacs.umd.edu Parallelism in computing: Parallel algorithmics; Synergy of algoithms, progamming and architecture for an easy-to-program general purpose parallel computer platform; Machine learning as well as other potential "killer applications" for parallel computing. Design and analysis of algorithms. Pattern matching. Theory of computing.
Tobias Von Petersdorff
tvp at math.umd.edu
Elliptic and parabolic boundary value problems; numerical methods.

Nonsmooth domains like polygons and polyhedra:
Singular behavior of the solution near edges and vertices, Efficient numerical approximation using Finite Element Methods, Boundary Element Methods and nonuniform meshes.
Multigrid and Wavelet techniques for Boundary Element Methods

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Stephen Wallace
stevewal at umd.edu
Dr. Wallace is a member of the Theory Group for Quarks, Hadrons, and Nuclei. The group conducts research in quantum chromodynamics, lattice QCD, hadron and nuclear physics.
Lawrence C. Washington
lcw at math.umd.edu
Number theory, cyclotomic fields, elliptic curves, cryptology
Michel Wedel   mwedel@rhsmith.umd.edu The application of Bayesian statistical and econometric methods to further the understanding of consumer behavior and to improve marketing decision making
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James A. Yorke
yorke at umd.edu
Professor Yorke's current research projects range from chaos theory and weather prediction and genome research to the population dynamics of the HIV/AIDS epidemic. For more detail see: http://yorke.umd.edu/current-projects.html Keywords:
Chaos, Weather Prediction, Genome, HIV/AIDS
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Michael R. Zachariah
mrz at umd.edu
Microcombustion, Energetic Materials and Reacting Flows (Combustion and Thermal CVD Processes). Fundamentals of Gas-Phase Chemical Kinetics: Measurement and Theory. Ab-Initio Computational Chemistry and Classical Molecular Dynamics. Numerical Simulation of Reacting Flows with Complex Chemistry Molecular-Beam and Single Particle Mass-Spectrometry.

Keywords:
NanoParticle Science, Manufacturing and Measurements.

Da-Lin Zhang
dalin at atmos.umd.edu
Prof. Zhang works on the modeling and understanding of fundamental processes taking place in squall lines, mesoscale convective complexes, hurricanes and heavy rain- (or snow-) storms, tropical and extratropical cyclones, gravity waves, frontal circulations and topographically generated weather phenomina. His research involves simulating a variety of different severe convective systems and cyclones; examining the meso-beta-scale structures and evolution as well as the mechanism(s) whereby they develop; testing theories, hypotheses and various model physical representations; and finally interpreting, to the extent possible, the observed behaviors of these weather systems. His research interests also include the development and improvement of the planetary boundary layer and cumulus parameterization techniques, cloud representations in mesoscale numerical models, and the improvement of warm-season quantitative precipitation forecasts and severe weather warnings.

Keywords:
Mesoscale Convective Systems, Tropical and Extratropical Cyclones, Mesoscale Modelling, Regional Climate, Air Pollution Meteorology

Wenlu Zhu                       wzhu at umd.edu Experimental rock deformation; Dynamic microtomography; Digital rock physics; Transport properities of partially molten rocks; Serpentinization and Carbonization of ultramafic rocks; fluid induced seismicity; Mechanics of slow slip events

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