Dr. Minh T. Huynh is Vice President of the IMPAQ Advanced Analytics Division. He currently provides oversight to the Data Science and Artificial Intelligence Group (DSAI) and is responsible for developing the division’s advanced analytics capabilities, business strategy, and research program.
Dr. Huynh has over 20 years of applied research experience, leading and participating in both theoretical and applied research projects for federal, state, and local governments and private companies. Dr. Huynh’s portfolio of work spans a number of computationally intensive methods, including microsimulation, high-performance scientific computing, applied machine learning methods, system dynamic models, agent-based models, applied graph theory and network analysis, automation, and emergent complex systems. In his leadership positions, Dr. Huynh excels at building interdisciplinary teams to use information-intensive tools to solve highly complex problems in both the public and private sector.
Since joining IMPAQ in 2014, Dr. has developed a robust portfolio of work in applied machine learning and advanced analytics of 45+ projects for a wide range of clients. Dr. Huynh’s portfolio includes the Agency for Healthcare Research and Quality; the National Institutes of Health (NIH); the U.S. Departments of Labor, Education, and Health and Human Services; the Social Security Administration; the Food and Drug Administration; Serco North America; Futrends, Inc.; New Wave Inc.; the District of Columbia Department of Employment Services; and the Newark Workforce Investment Board. Dr. Huynh is currently the Principal Investigator for two multiyear, multimillion dollar research projects to design, build, test, and validate microsimulation platforms for the U.S. Department of Education and the U.S. Department of Labor (DOL).
Prior to joining IMPAQ International, Dr. Huynh was the chief of the Office of Economic Policy and Analysis within the Office of the Assistant Secretary for Policy (OASP) at DOL. Dr. Huynh served as the chief economist of OASP and as the senior DOL economic advisor on technical problems, providing strategic policy advice to leadership and leading teams of economists to conduct economic impact analysis and costs-benefits analysis of proposed policies and regulations. Dr. Huynh came to DOL from the NIH Clinical Research Center (CRC), where he was a senior biostatistician and an institute staff scientist in the CRC’s Intramural Research Program. While at NIH, Dr. Huynh led a team of mathematicians, statisticians, computer scientists, and analysts to conduct a multimillion-dollar portfolio of intramural research, and he was the recipient of the 2011 NIH CRC Director’s Award for Science. While at the NIH, Dr. Huynh specialized in the analysis of statistical and design elements of clinical trials, review of experimental design and power analysis of experiments in clinical trials and treatment protocols, review and statistical analysis of functional and applied biomechanics trials, and other rehabilitation medicine projects. Dr. Huynh also led a team to analyze the disability determination process as part of an interagency agreement between the NIH CRC and the Social Security Administration.
Featured IMPAQ Publications and Presentations
Heuser, A., Huynh, M., and Zhou, C. (2016, February). Introduction to Adaptive Designs [Conference workshop]. American Statistical Association Conference on Statistical Practices, San Diego.
Kingi, H., Wang, L. A. D., Shafer, T., Huynh, M., Trinh, M., Heuser, A., ... & Paredes, A. (2020). A numerical evaluation of the accuracy of influence maximization algorithms. Social Network Analysis and Mining, 10(1), 1-10. September 2020.
Huynh, M., Heuser, A., Shetty, S., Zhang, S.,Trinh, M., Patterson,L., Miller, M., Kingi, H., Rochester, G., Parades, A.,) “A Stochastic System Dynamics Model for Tobacco Research” FDA/CTP/OS Statistics Branch Research Paper Series, No. 2019-01. January 2019.
Heuser, A., Huynh, M., & Chang, J. C. (2018) “A cohort-weighted Kaplan-Meier statistic for addressing random non-homogeneity in survival comparisons.” (with Heuser, A., & Chang, J. C.). Royal Society Open Science, Volume 5, November 1, 2018 https://doi.org/10.1098/rsos.180496 .
Huynh, M., Heuser, A., Shetty, S., Zhang, S.,Trinh, M., Patterson, L., Miller, M., Kingi, H., Rochester, G., Parades, A. “Agent-Based Models for Tobacco Research: A Literature Review.” FDA/CTP/OS Statistics Branch Research Paper Series, No. 2018-01. February 2018.
Huynh, M., Heuser, A., Shetty, S., Zhang, S.,Trinh, M., Patterson,L., Miller, M., Kingi, H., Rochester, G., Parades, A.,) “Social Network Analysis in Applied Tobacco Research: A Literature Review” FDA/CTP/OS Statistics Branch Research Paper Series, No. 2018-02. March 2018.
Huynh, M., Heuser, A., Shetty, S., Zhang, S.,Trinh, M., Patterson,L., Miller, M., Kingi, H., Rochester, G., Parades, A.,) “Influence Maximization: An Introduction and Literature Review for Tobacco Researchers” FDA/CTP/OS Statistics Branch Research Paper Series, No. 2018-03. March 2018.
Huynh, M., Heuser, A., Calahan, L., Moore, J.,.) “Recent Machine Learning Developments and Potential Applications for the United States Air Force Materiel Command: A White Paper”. 1st Place, Air Force Materiel Command White Paper Competition, US, March 2017.
Gerber, L. H., Weinstein, A. A., Frankenfeld, C. L., & Huynh, M. (2016). Disability among veterans: Analysis of the National Survey of Veterans (1997–2001). Military medicine, 181(3), 219-226, 2016.
Ciol, M. A., Rasch, E. K., Hoffman, J. M., Huynh, M., & Chan, L. (2014). Transitions in mobility, ADLs, and IADLs among working-age Medicare beneficiaries. Disability and health journal, 7(2), 206-215, 2014.
Collins, J., Huynh, M. (2014) “Estimation of diagnostic test accuracy without full verification: a review of latent class methods.” Statistics in Medicine, 2014 Oct 30;33(24):4141-69.
Rasch, E. K., Huynh, M., Ho, P. S., Heuser, A., Houtenville, A., & Chan, L. (2014). First in line: prioritizing receipt of social security disability benefits based on likelihood of death during adjudication. Medical care, 52(11), 944, 2014.
“Microsimulation Model for Paid Leave – an Application on Low-Wage Workers” Association for Public Policy Analysis and Management, 42nd Annual Fall Research Conference, Falls Church, Virginia, November 11-13 42nd, 2020.
“Applications of Text Analytics and Network Science In Regulatory Context” ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop, September 12-14, 2018 Washington, D.C.
“A System Dynamics Model For Tobacco Research” Presentation, American Statistical Association (ASA) Joint Statistical Meetings (JSM), July 28 – August 2, 2018 In Vancouver, British Columbia.
“Application of Ito Calculus and Mean Field Theory in Stochastic System Dynamics.” US Food and Drug Administration, Scientific Computing Workshop, September 7 2017, Silver Spring, Maryland.
Batch model for batched timestamps data analysis with application to the SSA disability program (with Q. Yue, A. Yuan, X. Che, E. Rasch , C. Zhou) Presentation, 22nd Association for Computing Machinery (ACM) Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) International Conference, August 13-17, 2016, San Francisco, California.