Clinical Research Machine Learning

Tom Burr, Curriculum Vita

Background

I have been team leader for hundreds of science projects, tasked to develop and implement statistical methods since joining Los Alamos National Laboratory after finishing my PhD in statistics from Florida State University in 1992. Example application areas include many types of machine learning (ML, including AI), time series, calibration, anomaly and signal detection related to nuclear, chemical, and biological threats, forensics, measurement error modeling with and without censoring, sequential testing, image analysis, sensor networks, measurement methods, computer model error, post-model-selection inference, remote sensing, process monitoring, material assay using neutron or gamma counting, and disease surveillance from classical and molecular epidemiological perspectives. I developed ML methods for fraud detection in Medicare claims, IRS claims, and collaborated with bioinformatics and molecular biology groups regarding population genetics, disease modeling and surveillance, and applications of phylogenetic trees to molecular epidemiology such as the origin of HIV. Most recently I was biostatistics subject matter expert for Tunnell, doing biostatistics reviews of medical device submissions to the FDA. One of my passions is to evaluate and improve the robustness of statistical approaches aiming to have a real impact on study conclusions, so I often use simulation in R. For example, I typically include the effects of model uncertainty on inference and confidence statements, and often use approximate Bayesian computation (ABC), particularly for its ability to accommodate model uncertainty. ABC is increasingly being used in ML as my book What to Tell the Grandkids about Data Science illustrates. Since 1992 I co-authored over 250 technical reports including more than 100 conference proceedings and more than 190 refereed articles, some of which are listed below. I frequently review papers for many journals including Applied Radiation and Isotopes, Technometrics, and is AE for BMC Medical Informatics and Decision Making, Chemometrics for Intelligent Laboratory Services, and Algorithms. Education

1992 Ph.D. Statistics Florida State University, Summa Cum Lauda, 3.9/4.0 1988 M.S. Statistics Florida State University, FSU Fellow, 3.9/4.0 1986 B.S. Physics University of North Carolina-Asheville, Summa Cum Lauda, 4.0/4.0 1981 B.S. Mathematics Clemson University, Summa Cum Lauda with honors, 3.9/4.0 Professional Qualifications

PhD. in Statistics, more than 30 years experience with a wide range of statistical methods including many types of Bayesian statistics and methods for censoring, experimental design, and multi-reader studies used in medical device and clinical studies. Approximately 2 year’s experience with clinical trial data and 1 year experience with medical device submissions to the FDA. Proficient in R. Some experience in SAS, python, matlab, and C++. Excellent communication skills and proven ability to describe statistical methods to broad audiences. Comfortable in a fast-paced environment and able to both delegate and perform work in a team setting.

Professional Experience

2023-2024 Biostatistics Subject Matter Expert, Tunnell Consulting to FDA on medical devices 2022-present Guest Scientist, Los Alamos National Laboratory (LANL) 1992-2022 Technical Staff Member LANL (and IAEA, Vienna 2014-2018) 1990-1992 Statistical Consultant, Florida State University Statistical Consulting Center 1981-1985 Physics and Math Instructor, Naval Nuclear Power School, Orlando, Florida LANL projects include multivariate sequential testing (Bayesian and non-Bayesian), nuclear data uncertainty, scanning for clusters in spatial time series using the Stein-Chen method, detecting fraudulent health-care claims by applying and developing pattern recognition techniques, and “filtering” out false alarms in vector-valued time series data of sensor data from satellites by applying and developing cluster analysis techniques, image analysis using conditional random fields. Professional Affiliations and Contributions

Senior Member Institute of Nuclear Materials Management Honorary lifetime member of Sigma Pi Sigma Honor Society of Physics Students Received 6-sigma course certificate through StraightLine Performance Solutions, 2009. Served on LANL directed research and development (LDRD) committee: 2009. Reviewed several small business grants under hyperspectral data analysis proposal calls.

Referee for many journals including: Journal of the Royal Statistical Society, Journal of the American Statistician Association, Technometrics, Nuclear Instruments and Methods in Physics Research, Applied Radiation and Isotopes, IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, Journal of Nuclear Materials Management. Statistics in Medicine, Bioinformatics, Sensors, IEEE Associate Editor, Mathematics and Engineering Techniques in Medicine and Biological Sciences, Environmental Science and Technology, BMC Medical Informatics and Decision Making, Analytical Chemistry, Mathematical Biosciences and Engineering, Mathematical and Computer Modelling, Encyclopedia of Data Warehousing and Mining, Transactions of the American Geophysical Union, Radio Science

Board member: (1) International Advisory Board for uncertainty in nuclear data and for (2) nondestructive assay.

Computing Experience

Extensive Fortran and R programming, one significant C++ project completed. Some programming in Python, Java and Visual Basic. Experience with several major statistical packages (in addition R) such as SPSS, BMDP, SAS, and Minitab while working as a statistical consultant at the Florida State University Statistical Consulting Center from August 1989-May 1992. My computational experience is good, including implementation of Markov Chain Monte Carlo methods to implement an empirical Bayesian approach to tomographic gamma scanning. As of 2020, I mainly use R. Teaching/Presentation

1981-1985 Taught math and physics to officers and enlisted, Naval Nuclear Power School 1988-1989 Taught undergraduate statistics courses (general) as FSU grad student. 1994-present: Prepared and presented two different in-depth (40 contact hours in 1 week) statistics in measurement control and nuclear safeguards courses for presentation in the former Soviet Union to technically trained (BS level or higher in scientific disciplines) nuclear facility personnel (1994). Organizer for course on statistical methods in safeguards presented annually since 1997. 1992-present: Frequent program-review presentations to both managers and technical people and presentation of papers at professional meetings.

Consulting while in Graduate School

Served from 1989-1992 as the Florida State University Consulting Center Research Assistant to the Director, Dr. Duane Meeter who was also my dissertation advisor. Consulting topics included: ANOVA, Design of Experiments, pattern recognition (classification), time series, and categorical data analysis. Clients: Primarily graduate students in education, psychology, biology, and business. Consulting for Florida Health Care Cost Containment Board, Florida Dept. of Health and Rehabilitative Services.

Awards/Grants/Fellowships

LANL Excellence Award: significant contributions to stockpile stewardship, 2007. Several small and large team project awards since 1992 at LANL. 2-5 grant proposals funded every year since 1992; Principal Investigator for ~100 LANL projects. Grant to present research on the origin of HIV/AIDS at the Royal Society Discussion on the Origins of HIV and the AIDS Epidemic, 2000

Los Alamos National Laboratory Distinguished Performance Awards: Internal Revenue Service Fraud Detection project, 1996; Materials Protection, Control and Accounting in the former Soviet Union, 1996. Grant to present sensor fusion research at Statistics in Chemistry Gordon Research Conference, New Hampton, New Hampshire, 1995

Grant to attend Statistical Methods in Molecular Biology Conference, Berkeley CA, 1992 Office of Naval Research Fellow 1986-1989

Florida State University Fellow 1986-1988

Most Outstanding Applied Statistics Ph.D. Student, 1986-1987, Florida State University Sue King Dunkle Mathematics Award, Clemson University 1981 R.F. Poole Alumni Scholar, Clemson University 1977-1981 References

Earl Lawrence, LANL Statistical Sciences, ****@****.*** James Gattiker, LANL Statistical Sciences, ****@****.*** Joanne Wendelberger, LANL Statistical Sciences, ******@****.*** Michael Hamada, LANL Statistical Sciences, ***@****.*** Christine Anderson-Cook, LANL Statistical Sciences, *-***-****@****.***. Claude Norman, International Atomic Energy Agency, *.******@****.*** Elisa Bonner, International Atomic Energy Agency, *.******@****.*** Refereed publications (a representative sample from more than 190 grouped by application) Measurement Error Modeling and Uncertainty

Lockhart M., Henzlova D., Burr T., Croft S., Favalli A., 252Cf Yield Calibration Method for Nuclear Material Accountancy and Safeguards Practitioners Nuclear Inst. and Methods in Physics Research A, Volume 1056, November 2023, 168648, 2023.

Vachhani S., Kalidindi S., Burr T., Pathak S., Lamellar Level Correlations between Mechanical Behavior and Composition in Mouse Bone, J. of Minerals, Metals, and Materials Society 73, 3034–3045, 2021. Bonner, E., Burr, T., Krieger, T., Martin, K., Norman, C., Santi, P., Uncertainty quantification in training courses for safeguards inspectors, ESARDA 62, 23-34, 2021. Wuster J., Norman C., Aregbe Y., Bencardino R., Burr T., Mason P. Walsh S., Alique O., Chapman J., Croft S., Fellerman A., Krieger T., Martin K., Probaska T., Trivedi D., Wegzynek D., Wright B., Statistical Error Model-Based and GUM-Based Analysis of Measurement Uncertainties in Nuclear Safeguards, ESARDA64, 1,10-29, 2022.

Trellue H., McMath G., Trahan A., Favalli A., Burr T., Sjoland A., Backstrom U., Spent Fuel Nondestructive Assay Integrated Characterization from Active Neutron, Passive Neutron, and Passive Gamma NIMA-D-20-00433R1, Nuclear Instruments and Methods in Physics Res A., 988, 164937, 2021. Burr T., Bonner E., Krzysztoszek K., Norman C., Setting Alarm Thresholds in Measurements with Systematic and Random Errors, Stats 2(2), 259-271, doi.org/10.3390/stats2020020, 2019. Burr, T., Martin, K., Norman., C, Zhao, K., Analysis of Variance for Item Differences in Verification Data with Unknown Groups, Science and Technol. of Nuclear Installations 2019, 1769149,doi/10.1155/2019/1769149, 2019.

Bonner, E., Burr, T., Norman, C., Peelle’s Pertinent Puzzle in Nuclear Safeguards Measurements, ESARDA Bulletin 57, 41-50, 2018.

Burr, T., Krieger, T., Norman, C., Approximate Bayesian Computation applied to Metrology for Nuclear Safeguards, ESARDA Bulletin 57, 50-59, 2018.

Bonner, E., Burr, T., Krieger, T., Martin, K., Norman, C., Comprehensive Uncertainty Quantification in Nuclear Safeguards, Science and Techn of Nuclear Installations, 1-16, 10.1155/2017/2679243, 2017. Agboraw, E. Bonner,E. Burr, T., Croft, S., Kirkpatrick, J., Krieger T., Norman, C. Santi, P Revisiting Currie’s Minimum Detectable Activity for Non-Destructive Assay by Gamma Detection Using Tolerance Intervals, ESARDA Bull 54,14-22, 2017.

Burr, T.,Croft, S., Krieger, T., Martin, K., Norman, C. Walsh, S., Uncertainty Quantification for Radiation Measurements: Bottom-Up Error Variance Estimation Using Calibration Information, Applied Radiation and Isotopes, 108,49-57, 2015.

Burr, T., Trellue, H., Tobin, S., Favalli, A., Dowell, J., Henzl, V., Mozin, V., Integrated Nondestructive Assay Systems to Estimate Plutonium in Spent Fuel Assemblies Nucl. Sci. Eng. 179(3), 321-332, 2015. Burr T., Croft S., Jarman K., Uncertainty Quantification in Application of the Enrichment Meter Principle for Nondestructive Assay of Special Nuclear Material, Journal of Sensors 15, Article ID 267462, http//dx.doi.org/10.1155/2015/26742, 2015.

Burr, T., Hamada, M.S, Analyzing Censored Data Multiplicative Repeatability and Reproducibility Studies, Accreditation and Quality Ass., 10.1007/s00769-014-1044-9, 19, 75–80, 2014. Burr, T., Hamada, M.S, Multiplicative Model for Gauge R & R Studies, Quality and Reliability Eng. Int 31, 801-809, 2015.

Croft, S., Burr, T., Calibration of Nondestructive Assay Instruments: An Application of Linear Regression and Propagation of Variance, Special Issue on Regression, Applied Math 5, 785-798, 2014. Burr, T., Hamada, M., Cremers, T., Weaver, B., Croft, S., Howell J., Vardeman, S., Rounding Error Effects in the Presence of Underlying Measurement Error, Accreditation and Quality Assurance Journal for Quality, Comparability and Reliability in Chemical Measurement, 17(5), 485-490, doi: 10.1007/s00769-012-0902-6, 2012.

Burr, T., Conlin, J., Galloway, J., Henzl, V., Hu, J., Menlove, H., Swinhoe, M., Tobin, S., Trellue, H., Ulrich, T., Uncertainty Quantification for New Approaches to Spent Fuel Assay, Nuclear Science and Engineering 172, 180-192, 2012.

Vardeman, S., Hamada M., Burr T., Wendelberger J., Moore L., Morris M., Wu H., Jobe M., Elementary Statistical Methods and Measurement Error, The American Statistician 64(1), 46–51, 2010. Burr, T., Hengartner, N., Matzner-Lober, E., Myers, S., Rouviere, L., Smoothing Low Resolution NaI Spectra, IEEE Transactions on Nuclear Science 57(5), 2831-2840, 2010. Burr, T., Hamada, M., Graves, T., Myers, S., Augmenting Real Data With Synthetic Data: an Application in Assessing Radio-Isotope Identification Algorithms, Quality and Reliability Eng Int 25:899-911, 2009. Burr, T., Butterfield, K., Variance Results for the Second and Third Reduced Moments in Neutron Multiplicity Counting for randomly triggered or signal-triggered counting gates, Nuclear Instruments and Methods in Physics Research A, 594(2), 257-265, doi:10.1016/j.nimaa.2008.06.010, 2008. Heasler, P., Burr, T., Reid, B., Gesh, C., Bayne, C., Estimation Procedures and Error Analysis For Inferring The Total Plutonium Produced by a Graphite-Moderated Reactor, Reliability Engineering and System Studies, 91, Issue: 10-11: 1406-1413, 2006. Burr, T., Charlton, W., Nakhleh, C., Assessing Confidence in Inferring Reactor Type and Fuel Burnup: A Markov Chain Monte Carlo Approach Nucl. Inst and Methods in Physics Res. 555, 1-2: 426-434, 2005. Burr, T., Sampson, T, Vo, D., Statistical Evaluation of FRAM -ray Isotopic Analysis Data, Applied Radiation and Isotopes 62, 931-940, 2005.

Machine Learning

Shoman N., Vollmera C., Burr T., Impact of Measurement Error on Deep Neural Networks for Safeguards Applications, Nuclear Engineering and Design, Vol402, Feb 2023, 112113, 2023. Akcay C., Finn J., Brennan D., Burr T., Kurkcuoglu D., Machine Learning Methods for Forecasting Error-Field Locking in Tokamak Plasmas, Physics of Plasmas, 28, 082106 (2021); doi: 10.1063/5.0053670, 2021.

Burr, T., Dowell, J., Trellue, T., Tobin, S., Measuring the Effects of Data Mining on Inference, Encyclopedia of Information Science and Technology, Third Edition, Mehdi Khosrow-Pour (Information Resources Management Association, USA), Chapter 176, 1825-1833, 2014. Burr, T., Hamada, M.S., Myers, K, Hengartner, N., Picard, R., Data Mining in Radiation Portal Monitoring, International Journal of Research and Reviews in Applied Science 17(1), 1-8, 2013. Burr, T., Hamada, M.S., Data Analysis in Support Of Radiation Portal Monitoring, International Journal of Research and Reviews in Applied Science, 14(1), 1-16, 2012. Burr, T., Hamada, M.S., Skurikhin, M., Weaver, B., Pattern Recognition Options to Combine Process Monitoring and Material Accounting Data In Nucl. Safeguards, Statistics Res. Letters 1(1), 6-31, 2012. Burr, T., Hamada, M., Song, J., Wolinsky, M., Special Topics in Pattern Recognition with Applications in Nonproliferation book Chapter on Pattern Recognition, Nova Science, 2011. Burr, T, Hamada, M., Radio-isotope Identification Algorithms for NaI Gamma Spectra, Algorithms 2(1): 339-360, 2009.

Burr, T., Cluster Analysis in Fitting Mixtures of Curves, Encylopedia of Data Mining 2nd Ed, 2008. Burr, T., Myers, K., Signatures for Several Types of Naturally Occurring Radioactive Material, Applied Radiation and Isotopes 66: 1250-1261, 2008.

Burr, T., Fry, H., McVey, B., Sander E., Cavenaugh J., Neath A., Performance of Variable Selection Methods in Regression Using Variations of the Bayesian Information Criterion, Comm. in Stat- Simulation 37:507-520, 2007.

Burr, T., Doak, J., Distribution Free Discriminant Analysis, Data Analysis, 11(6): 651-662, 2007. Burr, T., Pickrell, M., Rinard, P.,Wenz,T., Data Mining: Applications to Nondestructive Assay Data, Journal of Nucl. Mater. Manage.27(2), 40-47, 1999. Burr T, Dreicer J, Pickrell M.,Shielding-Related Assay Challenges and Experimental Results in Nuclear Safeguards, American Nuclear Society Trans. Am. Nucl. Soc. 81, 240-241, (invited paper), 1999. Time Series

Burr T., Kaufeld K., Change Detection by Monitoring Residuals from Time Series Models, Mathematical Concepts of Forecasting, InTech, 2022

Burr T., Henderson B., Scanning for Clusters of Large Values in Time Series: Application of the Stein- Chen Method. Applied Mathematics 12, 1031-1037, 2021. Burr, T., Hamada, M.S, Ticknor, L, Weaver, B., Model Selection and Change Detection for a Time- Varying Mean in Process Monitoring, Nuclear Inst, and Methods in Physics Res. A, 751, 79-87, 2014. Burr, T., Hamada, M.S., Smoothing and Time Series Modeling of Nuclear Material Accounting Data for Protracted Diversion Detection, Nuclear Science and Engineering 177, 307–320, 2014 2014. Burr, T., Hamada, M.S., Howell, J., Skurikhin, M., Ticknor, L., Weaver, B. Estimating Alarm Thresholds for Process Monitoring Data Under Different Assumptions About the Data Generating Mechanism, Science and Technology of Nuclear Installations, Volume 2013, Article ID 705878, 18 pages, http://dx.doi.org/10.1155/2013/705878, 2013.

Reliability

Blanchard S., Burr T., DeBardeleben N., Loncaric J., Penton, S., Performance Testing High Performance Computers, IEEE/ACM 11th Workshop on Fault Tolerance for HPC at Extreme Scale SC p 21-30,2021. Burr, T., Hamada, M., Cremers, T., Weaver, B., Croft, S., Howell J., Vardeman, S., Rounding Error Effects in the Presence of Underlying Measurement Error, Accreditation and Quality Assurance Journal for Quality, Comparability and Reliability in Chemical Measurement, 17(5), 485-490, doi: 10.1007/s00769-012-0902-6, 2012.

Burr, T., Hamada, M., Cremers, T., Weaver, B., Croft, S., Howell J., Vardeman, S., Rounding Error Effects in the Presence of Underlying Measurement Error, Accreditation and Quality Assurance Journal for Quality, Comparability and Reliability in Chemical Measurement, 17(5), 485-490, doi: 10.1007/s00769-012-0902-6, 2012.

Forensics

Burr T., Schwerdt I., Sentz K., McDonald L., Wilkerson M., Overview of Algorithms for Using Particle Morphology in Nuclear Forensics, Algorithms 14(12), 340, doi.org/10.3390/a14120340, 2021. Thomas, E., Lewis, J., Anderson-Cook, C., Burr, T., Hamada, M.S., Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction, J. Quality Technology, 2017. Anderson-Cook C., Burr T., Hamada, M.S. Ruggiero, C., Thomas E., Design of Experiments and Data Analysis Challenges in Calibration for Forensics Applications, Chemometrics and Intelligent Laboratory Systems, 149(B), 107-117, 2015.

Anderson-Cook C., Burr T., Hamada M.S., Impact of Response Measurement Error on Analysis of Designed Experiments, Quality and Reliability Engineering DOI:10.1002/qre.1945, 2015. Anderson-Cook C., Burr T., Hamada M.S., Thomas E., Statistical Analysis for Nuclear Forensics Experiments, Statistical Analysis and Data Mining, 8(5-6), 364-377, 2015. Song, J., Doggett, N., Henrie, M., Burr, T., Fenimore, P., Bruno, W., Li, P., Gans, J., Stubben, C., Wolinsky M., Development of Forensic Assay Signatures for Ebolaviruses Journal of Forensic Science DOI: 10.1111/1556-4029.12655, 2015.

Song, J., Wolinsky M., Henrie M., Burr T., Li, P., Gans J., Stubben C., Doggett N., Forensic Signatures for Marburgviruses, Forensic Science International, 233, (1–3), 338-347, 2013. Nuclear, Biological, Chemical NonProliferation Applications Burr, T., Croft, S., Williams, B., White, M., Hanson, K., Meta-analysis Options for Inconsistent Nuclear Measurements, Nuclear Science and Engineering, 171(1), 15-27, 2013. Burr, T., Skurikhin, A., Selecting Summary Statistics in Approximate Bayesian Computation for Calibrating Stochastic Models, BioMed Research International, vol. 2013, Article ID 210646, 10 pages, 2013. doi:10.1155/2013/210646, 2013.

Burr, T., Hamada, M., Moving Neutron Source Detection in Radiation Portal Monitoring, Technometrics 55(3), 296-308, 2013.

Picard, R., Burr, T., Hamada, M., Alarm Threshold Estimation for Radiation Portal Monitoring, Technometrics 55(1), 94-102, 2013.

Burr, T., Hamada, M., Myers, K., Skurikhin, M., Point Source Detection Using Gamma Ray Spectra in Radiation Portal Monitoring, Journal of Quality Technology, 45(3), 285-296, 2013. Burr, T., Skurikhin, A., Selecting Summary Statistics in Approximate Bayesian Computation for Calibrating Stochastic Models, BioMed Research International, vol. 2013, Article ID 210646, 10 pages, 2013. doi:10.1155/2013/210646, 2013.

Longo, C., Burr, T., Myers, K. Change Detection using Wavelets in Solution Monitoring Data for Nuclear Safeguards Axioms, 2(2), 271-285; doi:10.3390/axioms2020271, 2013. Hamada, M., Lohr, S., Hamada, C., Burr, T., Estimating a Proportion from Repeated Sampling of a Growing Population, Quality Engineering, 25, 108-117, 2013. Burr, T., Hamada, M., Finding Test Statistic Thresholds Using Simulation and Model Fitting with an Application to Radiation Detection, Quality Engineering 24(3), 2012. Burr, T., Kuhn, K., Tandon, L., Tompkins, D., Measurement Performance Assessment of Analytical Chemistry Analysis Methods using Sample Exchange Data, Intern. J.Chem. 3(4), 10.5539/n4p40, 2012. Burr, T., Hamada, M., Estimating Alarm Thresholds and the Number of Components in Mixture Distributions, Nuclear Instruments and Methods in Physics Research A, 685, 55-61, 2012. Burr, T., Smith-Nelson, M., Experimental Verification of Variance Results for the Second and Third Reduced Factorial Sample Moments in Neutron Multiplicity Counting, International Journal of Research and Reviews in Applied Science 13(2), 353-357, 2012. Burr, T., Suzuki, M., Howell, J., Hamada, M., Longo, C., Signal Estimation and Change detection in Tank Data for Nuclear Safeguards, Nucl. Instr. and Methods in Physics Research 640 200–221, 2011. Burr, T., Hamada, M., Hengartner, N., Impact of Spectral Smoothing on Gamma Radiation Portal Alarm Probabilities, Applied Radiation and Isotopes 69, 1436-1446, 2011. Garcia, H., Burr, T., Coles, G., Edmunds, T., Garrett, A., Gorensek, M., Hamm, L., Krebs, J., Kress, R., Lambertia, V., Schoenwald, D., Tzanos, C., Ward, R. Integration of Facility Modeling Capabilities for Nuclear Nonproliferation Analysis, Progress in Nuclear Energy, 54(1), 96-111, 2011. Burr, T., Kawano, T., Talou, P., Pen, F., Hengartner N., Graves T., Alternatives to the Generalized Least Squares Solution to Peele’s Pertinent Puzzle, Algorithms 4(2), 115-130, 2011. Burr T., Kawano T., Talou P., Pen F., Hengartner N., Defense of the Generalized Least Squares Solution to Peele’s Pertinen t Puzzle, Algorithms 4(1), 28-39, 2011. Burr, T., Weier, D., Hypothesis Testing: Frequentist Versus Bayesian with Examples From Nuclear Safeguards, Journal of Nucl. Mater. Management, 37(2): 16-22, 2009. Burr, T., Myers, K., Background Suppression Effects on Signal Estimation, Applied Radiation and Isotopes 67:1729-1737, 2009.

Picard, R., Burr, T., Networked Sensors for Cargo Screening, IEEE Sensors 8(8):1389-1396, Aug 2008. Tandon, L, Kuhn, K., Tompkins, D., Burr, T., Temer, D., Hastings, E., Porterfield, E., Wong, A., Fonnesbeck, J., Narayanan, U., Neuhoff, J., Torres, R., Holland, M., Actinide analytical chemistry, past, present and future, Transactions of the American Nuclear Society, 97, 259-260, 2007. Burr, T., Gattiker, J., Myers, K., Tompkins, G., Alarm Criteria in Radiation Portal Monitoring, Applied Radiation and Isotopes, 65: 569–580, 2007.

Burr, T., Fry, H., Biased Regression: Case for Cautious Application, Technometrics 13, 284-296, 2005. Burr, T., Jacobson, A., Mielke, A., Dynamic Global Radio Frequency Noise Survey as Observed from the FORTE Satellite at 800-km Altitude, Radio Science 40(6), RS6016, 10.1029/2005RS003246, 2005. Burr, T., Krick, M., Mielke, A., Statistical Evaluation of Two Triggering Systems: an Application of Conditional Variance, Nucl. Inst and Methods in Physics Research A 524: 314-323, 2004. Burr, T., Jacobson, A., Mielke, A., A Global Radio Frequency Noise Survey as Observed from the FORTE Satellite at 800-km Altitude, Radio Science 39, RS 4005, doi:10.1029/2002RS002865, 2004. Burr, T., Quasi-Equilibrium Theory for the Distribution of Rare Alleles in a Subdivided Population: Justification and Implications, Theoretical Population Biology 57(3): 297-306, 2000. Image Analysis

Burr T., Skurikhin A., Conditional Random Fields for Pattern Recognition Applied to Structured Data, Algorithms, 8, 466-483; doi:10.3390/a8030466, 2015. Burr, T., Skurikhin, A., Pseudo-likelihood Inference for Gaussian Markov Random Fields, Statistical Research Letters 2(3), 63-68, 2013.

Burr, T., Hengartner, N., Overview of Physical Models and Statistical Approaches for Weak Gaseous Plume Detection Using Infrared Hyperspectral Imagery, Sensors 6: 1721-1715, mdpi.org/sensors/list06.htm#issue12, 2006.

Burr, T., Foy, B., Fry, H., McVey, B., Characterizing Clutter in the Context of Detecting Weak Gaseous Plumes in Hyperspectral Imagery, Sensors 6: 1587-1615, 2006, mdpi.org/sensors/list06issue11, 2006. Classical Epidemiology

Burr, T., Michalak, S., Picard, R., Statistical Challenges in BioSurveillance, in Mathematical and Statistical Estimation Approaches in Epidemiology, Springer, Netherlands, Editors: Chowell, G., Hyman, J., Bettencourt, L, Castillo-Chavez, C., 2009.

Burr, T., Chowell, G., Daily Estimation of the Reproduction Number Rt in Structured and Nonstructured Populations, Mathematical Biosciences and Engineering 6(2), 239:259, 2009. Burr, T., Chowell, G., Signatures of Inhomogeneity in Disease Outbreaks, Math and Computer Modelling 48:122-140, 2008.

Burr, T., Data Mining in Genome Wide Association Studies, Encylopedia of Data Mining, 2nd Ed, 2008. Burr, T., Koster, F., Picard, R., Forslund, D., Wokoun, D., Joyce, E., Brillman, J., Froman, P., Lee, J., Computer-Aided Diagnosis with Potential Application to Rapid Detection of Diseases Outbreaks, Statistics in Medicine 26: 1857-1874, 2007.

Burr, T., Graves, T., Klaman, R., Michalek, S., Picard, R., Hengartner, N., Accounting for Seasonal Patterns in Syndromic Surveillance Data for Outbreak Detection, BioMedCentral, Medical Informatics and Decision Making, 6:40, 2006.

Forslund, D., Joyce, E., Burr, T., Picard, R., Wokoun, D., Umland, E., Brillman, J., Froman,P., Koster, F., Setting Standards for Improved Syndromic Surveillance, IEEE Engineering in Medicine and Biology Magazine 65-70, Jan/Feb 2004.

Burr, T., Chowell, G., Observation and Model Error Effects on Parameter Estimates In Susceptible- Infected-Recovered Epidemiological Models, Journal of Theoretical Statistics 19(2): 163-183, 2006. Burr, T., Gattiker, J., The Impact of Model Uncertainty on Biological Parameter Estimates, Far East Journal of Theoretical Statistics, 13(2) 153-174, 2005. Brillman, J., Burr, T., Forslund, D., Joyce, E., Picard, R., Umland, E., Modeling Emergency Department Visit Patterns for Infectious Disease Complaints: Results and Application to Disease Surveillance, BioMedCentral, Medical Informatics and Decision Making 5, 4, 2005. Burr, T., Maximally Selected Measures of Evidence of Disease Clustering, Statistics in Medicine, 20, 1443-1460, 2001.

Charlton, W., Burr, T., Stanbro, W., Budlong-Sylvester K., Gattiker J., Simulation Tool for Predicting Classical Epidemiology Data for Infectious Diseases Using a Probabilistic Model, Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences, 489-495, 2000.

Molecular Epidemiology

Burr,T., Predicting Virus Evolution, Ch13, 269-287, Bioinformatics:Methodologies, InTech, 2011. Burr, T., Phylogenetic trees in Bioinformatics, Current Bioinformatics 5(1),40-52, 2010. Burr,T., Methods for Choosing Clusters in Phylogenetic Trees, Enc. Data Mining John Wang, ed., 2005. Burr, T., Gattiker, J., Gerrish, P., An Investigation of Error Sources and Their Impact in Estimating the Time to the Most Recent Ancestor of Spatially and Temporally Distributed HIV Sequences, Statistics in Medicine 22(9):1495-1516, 2003.

Burr, T., Gattiker, J., LaBerge, G., Genetic Subtyping using Cluster Analysis, Special Interest Group on Knowledge Discovery and Data Mining Explorations, 3, 33-42, 2002. Burr, T., Doak, J., Gattiker, J., Stanbro, W., Assessing Confidence in Phylogenetic Trees: Bootstrap versus Markov Chain Monte Carlo, Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences, Vol 1, 181-187, 2002. Burr T., Hyman J., Myers G., The Origin of Acquired Immune Deficiency Syndrome: Darwinian or Lamarckian?, Phil Trans R Soc London B Biological Science Jun 29;356(1410):877-87, 2001. Burr, T., Charlton, W., Stanbro, W., Comparison of Signature Pattern Analysis Methods in Molecular Epidemiology, Proceedings of the International Conference on Math and Engineering Techniques in Medicine and Biological Sciences, 473-479, 2000.

Burr, T., Skurikhin, A., Bruno, W., Macken, C., Confidence Measures for Evolutionary Trees: Applications to Molecular Epidemiology. Proc. IEEE Inter. Conf. on Information, Intelligence and Systems, Genetics and Evolution Section 107-114, 1999. Skurikhin, A., Burr, T., Linguistic Analysis of

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