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Department of Mathematical Sciences. 40 Faculty 41 Graduate Students Approximately 80 Undergraduate Students. Applied Mathematics Statistics Combinatorics and Pure Math Mathematics Education. Research Areas. Applied Mathematics Computational Engine Research – F. Tanner
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40 Faculty • 41 Graduate Students • Approximately 80 Undergraduate Students
Applied Mathematics Statistics Combinatorics and Pure Math Mathematics Education Research Areas
Applied Mathematics Computational Engine Research – F. Tanner Simulation of Food Sprays – F. Tanner Multiphase Fluid Systems – K. Feigl Cardiac Dynamics – W. Ying Computational Biology – L. Zhang March 2008 Computing Initiative
Computational Engine Research • Modeling of flow, spray and combustion processes Prof. Franz Tanner
Motivation • Health and Environmental • Sustainability • Main Objectives • Understand physical processes • Develop simulation tools • Results • Strategy to minimize fuel consumption and emissions • Multi-orifice asynchronous injection Computational Engine Research Mass fraction of an evaporating fuel spray
Motivation • Spray-drying and spray-freezing • Encapsulation of nutrients • Main Objectives • Obtain desired drop size distributions • Maximize production • Modeling Challenges/Research • Complex flows and materials • Phase changes Modeling of Food Sprays Air-assisted atomization of a nutriose liquid spray
Simulation of flow of complex fluids • Collaborations with ETH-Zurich and University of Tennessee Prof. Kathleen Feigl
Examples/Applications • Emulsions, foams, polymer blends • Foods, plastics, pharmaceuticals • Goals • Understand process-microstructure- rheology relationship • Design processes to optimize product properties • Research • Multidisciplinary approach • Combine modeling, simulation and experiments Simulation of Fluid Systems Simulated deformation of a fluid droplet March 2008 Computing Initiative
Simulation of Fluid Systems Droplet deforming in supercritical shear flow Droplet deforming in supercritical elongational flow
Ph.D. – Duke • Joined MTU Fall 2008 • Research Interests • Scientific Computing • Modeling/Simulation • Mathematical Biology • CFD Wenjun Ying, Asst. Prof.
Space-time adaptive mesh refinement • Multi-scale adaptive modeling of electrical dynamics in the heart Simulation of Cardiac Dynamics Simulation of wave propagation in a virtual dog heart
Beating heart Droplet deformation Multiphase flows Other free-boundary or moving interface problems Cartesian Grid Method Grid lines not aligned with complex domain boundary
Ph.D. – Louisiana Tech • Post-doc – Harvard/MIT • Joined MTU Fall 2008 • Research Interests • Computational biology • Cluster and classification algorithms • Software application development Le (Adam) Zhang, Asst. Prof.
Performing multi-scale, multi-resolution hybrid cancer modelling • Regression analysis, multivariate analysis Simulation of Brain Cancer Progression Brain Cancer Cell Simulation of Cancer Progression
Simulate bio-heat transfer by finite difference method Inverse heat convection problem Simulation of Hyperthermia in Skin Cancer Treatment Skin Cell Structure Treatment Simulation
Statistics Statistical Genetics – Q. Sha, R. Jiang, J. Dong, S. Zhang, H. Chen Wildlife Population Studies – T. Drummer Statistics , Probability, Optimization – I. Pinelis Statistical Methodolgy and Data Analysis – Y. Munoz –Maldonado March 2008 Computing Initiative
Population studies for moose, wolves and sharp-tail grouse in U.P. • Aerial Observation Prof. Tom Drummer
Moose survey conducted at 500 ft altitude over 1600 sq. mile area • Model developed to yield probability of sighting animals
Ph.D. – Texas A&M University • Statistical Methodology and Analysis of Data • Functional Data Analysis • Non parametric Methods • Linear and Mixed Models • Multivariate Analysis Yolanda Munoz-Maldonado, Asst. Prof.
Ganglioside Profiles Analysis • Detect differences in brains of young and old rats • Differences found in locus coeruleus of young rats which may affect sleep regulation
Study of effect of chronic exposure to particulate matter on mortality • Temporal analysis of PM10 in El Paso, TX • Study suggests use a principal component analysis
Statistical Genetics Group • 5 Faculty • 2 Post – docs • 9 PhD Students • Support from NIH and NSF
Statistical Genetics Group • Sixteen Members • 5 faculty • 2 post-docs • 9 PhD Students • Supported by 4 NIH Grants • Total funding of over $1 million
Statistical Genetics Group Group Aims • Develop new tools for analysis of genomic data • Use innovative models and methods in human genetic studies Key Research Areas • Functional gene mapping • Pedigree analysis • Gene interactions • Computational methodologies • Microarray analysis
Statistical Genetics • Prof. Quiying Sha • PhD Student Elena Kasyanova