Associate Research Professor of Computational Engineering

Chad Eric Burdyshaw

**** * ****** ** ****: 423-***-****

Signal Mtn. TN 37377 email:

*************@*******.***

Summary

Computational Research Scientist with fifteen years of experience in large

scale model development and optimization. Driven by keen scientific

curiosity to investigate new ideas and solutions using sound statistical

and computational techniques. Diverse industry experience, including health

care, biomedical, alternative energy, and aerospace engineering.

Highlights

. Diverse skill set in computational math and scientific methods; highly

adept at utilizing programming skills, software packages, and analytic

thinking to gain real-world insights

. Development of data analytics projects in risk prediction and

preventative health care

. Mentor and teacher to graduate-level computational engineering students

. Experienced in a variety of programming languages, including R, Shiny,

Python, C/C++, FORTRAN, MPI, OpenMP

. Subject matter expert invited to present before NATO conference in

Athens, Greece

. Selected for fellowship to advance high performance computing skills at

Argonne National Laboratory

. Experience with a variety of data mining techniques (linear/logistic

regression, decision trees, SVM, random forest, neural networks,

Bayesian regression, ensembles, clustering: hierarchical, k-means,

DBScan)

Employment

University of Tennessee at Chattanooga

SimCenter National Center for Computational Engineering

Chattanooga, Tennessee 2002-Present

Associate Research Professor, 2011-Present

. Research and development of methods related to computational design and

optimization for complex multiphysics models on large scale distributed

computing architectures. Investigated languages and applications for

analytics and machine learning algorithms in a shared memory

multiprocessing environment

. Principal Investigator and recipient of several grants

. Courses Taught: Engineering Programming, ENEE 2250

. Recent Collaborations: Siskin Rehabilitation Center to identify risk

factors for post-rehab medical complications; UTC Department of Health

and Human Performance and School of Business at UTC, sports medicine

injury risk assessment and prevention.

Assistant Research Professor, 2006-2011

. Research and development of methods related to computational design

. Projects: Fuel Cell fluid distribution optimization; Design of metal

stent in turbulent arterial flow; Large scale linear systems solvers;

Electromagnetic field simulation and design code; Drag reduction

simulations for tractor trailers.

Research Associate, 2002-2006

. Research on methods for large scale multivariable sensitivity analysis,

uncertainty quantification, design, and optimization.

. Developed novel approach to automate large scale code development for

sensitivity analysis capabilities.

Mississippi State University

Department of Computational Engineering

Starkville, Mississippi

1999-2002

Research Associate, 2001-2002

. Research and development of design optimization methods for aerospace and

naval applications

Graduate Research Assistant, 1999-2001

. Investigation of methods for low fidelity turbomachinery shape design.

. Developed parallel genetic optimization algorithm

. Developed novel computational method for sensitivity analysis

Accelerations Software,

Poulsbo, Washington 1999

Software Engineer, May- September

. Software testing and development on Linux, Windows, MacOS; Compiler

design and language processing

Pacific Northwest National Laboratory

Richland, Washington 1997

Undergraduate Research Assistant, May- August

. Experimental research in non-destructive testing and material

identification

. Investigated mathematical methods for signal processing

Education

. Ph.D. Computational Engineering

University of Tennessee at Chattanooga

2006

. M.S. Computational Engineering

Mississippi State University

2001

. B.S. Physics

Central Washington University 1999

. B.S. Computer Science

Central Washington University 1999

. Continuing education via formal workshops and MOOCs:

Skills Learned: Machine learning and data mining methods: Linear/Logistic

regression, Bayesian, Decision Trees, Random Forest, SVM, Neural

Networks, Ensemble methods, Information retrieval and decision support,

text analysis, Clustering and graph analysis

o Argonne National Laboratory Training Program for Extreme Scale

Computing

. Programming for hybrid architectures and fine grain

parallelism

o Coursera- Johns Hopkins Data Science Specialization:

Getting and Cleaning Data; Exploratory Data Analysis;

Reproducible Research; Statistical Inference; Regression Models;

Practical Machine Learning; Developing Data Products

o Coursera-Urbana Champaign Data Science Specialization:

Pattern Discovery in Data Mining; Text Retrieval and Search

Engines; Cluster Analysis; Text Mining; Visualization

o EdX-Berkeley Artificial Intelligence

. Decision Theory, Markov Decision Processes, Reinforcement

Learning

o Coursera- Stanford Machine Learning

. Neural Networks, SVM, Strategies for Big Data, Validation,

System Design

o Coursera- Stanford Mining Massive Datasets

. Map-Reduce, Page Rank, LSH, Streams, Clustering,

Dimensionality Reduction

o EdX- MIT Analytics Edge

. Applied machine learning in R and Excel

o EdX- MIT Computational Thinking and Data Science

. Python for data science

Additional Research Activities and Experience

. Relational database experience, SQL; Familiarity with Non-Relational

database, NoSQL (MongoDB, Cassandra) ; Experience with "big data" cluster

environments (Hadoop, Spark)

. Stochastic and deterministic model optimization algorithms on high

performance computing platforms (Genetic Algorithms, Simulated Annealing,

Quasi-Newton, Interior Point Methods)

. Development of advanced numerical mathematics methods applied to

nonlinear PDEs, matrix algebra methods, numerical integration, and domain

discretization

Honors & Activities

. University of Tennessee at Chattanooga Big Data and Analytics Research

Center (BDARC) Affiliated Faculty

. Argonne Extreme Scale Computing Fellowship, 2014

. Presenter, 2007 NATO RTO-AVT-147 meeting on Computational Uncertainty in

Military Vehicle Design.

. Presenter, 43rd AIAA Aerospace Sciences Meeting and Exhibit, 2005

. MSU External Research Advisory Committee Presenter

. NSF Engineering Research Center Advisory Committee Presenter

. MSU Engineering Research Center Graduate Student Council Officer

. Associated Western Universities Research Fellowship

. Magna Cum Laude graduate in Physics and Computer Science

. First "Outstanding Computer Science Graduate" awarded by CWU

. Society for Physics Students Chapter Officer

. Member Sigma Pi Sigma Physics Honor Society

Peer-Reviewed Publications and Creative Works

. Gupta, A., Burdyshaw, C., Kapadia, S., Young, C., "A Predictive Analytics

Approach for Improved Rehabilitation Care Outcomes", International

Conference on Big Data & Analytic for Business, New Delhi, India, Dec

2014.

. Brock, W., Burdyshaw, C., Karman, S., Betro, V., Hilbert, B., Anderson,

K., Haimes, R., "Adjoint-Based Design Optimization Using CAD

Parameterization Through CAPRI", AIAA-2012-968, 50th AIAA Aerospace

Sciences Meeting, Nashville, TN, January 2012.

. Kapadia, S., Anderson, W.K., and Burdyshaw, C., "Channel shape

optimization of solid oxide fuel cells using advanced numerical

techniques," Computers & Fluids, Vol. 41, 2011, 41-50.

. Kapadia, S., Anderson, W. K., and Burdyshaw, C., "Channel Shape Design of

Solid Oxide Fuel Cells," UTC-CECS-SimCenter-2009-01, June 2009.

. Anderson, W.K., Karman, S.L., and Burdyshaw, C., "Geometry

Parameterization Method for Multidisciplinary Applications," AIAA

Journal, Vol. 47, No. 6, June 2009.

. Kapadia, S., Anderson, W. K., Elliott, L., and Burdyshaw, C., "Adjoint

based Sensitivity Analysis and Error Correction Methods applied to Solid

Oxide Fuel Cells," ASME Journal of Fuel Cell Science and Technology, Vol.

6, No. 2, 2009.

. Anderson, W. Kyle, Karman, Jr., S.L., and Burdyshaw, Chad, "Geometry

Parameterization Using Control Grids," AIAA 2008-Presented at the 12th

AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference,

Victoria, BC, September 10-12, 2008.

. W.K. Anderson, Steve L. Karman, C. Burdyshaw," Geometry Parameterization

Using Control Grids", AIAA Paper 2008-6028.

. Burdyshaw, C.E.; Anderson, W.K., "Advances in Discrete Sensitivity

Methods Applied to Uncertainty Analysis", Proceedings of NATO RTO-AVT-147

meeting on Computational Uncertainty in Vehicle Design. Athens, Greece.

December 2007.

. S. Kapadia, W.K. Anderson, L. Elliott, C. Burdyshaw, "Adjoint method for

solid-oxide fuel cell simulations", Journal of Power Sources, Vol. 166,

2007, pp. 376-385.

. S. Kapadia, W. K. Anderson, L. Elliott and C. Burdyshaw, "Adjoint Based

Sensitivity Analysis And Error Correction Methods Applied To Solid Oxide

Fuel Cells", Presented at ASME 5th International Fuel Cell Science,

Engineering & Technology Conference, June 18 - 20, 2007, New York,

FuelCell 2007-25157.

. C. Burdyshaw, "Achieving Automatic Concurrency Between Computational

Field Solvers and Adjoint Sensitivity Codes". Ph.D. Thesis, University of

Tennessee at Chattanooga, 2006

. C. Burdyshaw, W.K. Anderson, "A General and Extensible Unstructured Mesh

Adjoint Method". AIAA Journal of Aerospace, Computing, Information, and

Communication. 2005.

. C. Burdyshaw, "Quasi 3-D Multi-Stage Turbomachinery Pre-Optimizer".

Masters Thesis, Mississippi State University, 2001.

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