Dr. Lianfen Qian is a distinguished biostatistician and Professor of Practice at the University of Arizona, with extensive expertise in developing and applying statistical methodologies to biomedical, environmental, and genomic research. She earned her B.S. and M.S. in Mathematics and Statistics from Zhejiang University, China, and her Ph.D. in Statistics from Michigan State University. Dr. Qian’s research focuses on survival analysis, longitudinal data modeling, semi-competing risks, and structural change detection. Her work has been widely published in leading journals such as Biometrika, Computational Statistics & Data Analysis, and Frontiers in Cellular and Infection Microbiology. A seasoned educator and mentor, she has guided numerous Ph.D. and M.S. students, with one of her mentees earning first place in the 2015 ASA/CAUSE Undergraduate Research Project Competition. She has also served in leadership roles for the American Statistical Association’s South Florida Chapter and contributed as an NSF panelist. Dr. Qian’s career includes academic appointments at Florida Atlantic University and Lynn University, along with her leadership of Mathematics and Data Science, LLC. Her numerous honors include the ASA Award for Outstanding Chapter Service, NSF travel and research awards, and recognition in Who’s Who in America. She has collaborated on research projects funded by the NSF, NCI, and DoD, and continues to contribute to advancing data-driven research and interdisciplinary science. (Document: Lianfen Qian,
Profiles: Scopus | ORCID | Google Scholar
Featured Publications
1. Heilmayer, O., Digialleonardo, J., Qian, L., & Roesijadi, G. (2008). Stress tolerance of a subtropical Crassostrea virginica population to the combined effects of temperature and salinity. Estuarine, Coastal and Shelf Science, 79(1), 179–185. Cited by 100.
2. Wang, S., Qian, L., & Carroll, R. J. (2010). Generalized empirical likelihood methods for analyzing longitudinal data. Biometrika, 97(1), 79–93. Cited by 78.
3. Koul, H. L., Qian, L., & Surgailis, D. (2003). Asymptotics of M-estimators in two-phase linear regression models. Stochastic Processes and Their Applications, 103(1), 123–154. Cited by 72.
4. Gan, W., Bragg, F., Walters, R. G., Millwood, I. Y., Lin, K., Chen, Y., Guo, Y., … (2019). Genetic predisposition to type 2 diabetes and risk of subclinical atherosclerosis and cardiovascular diseases among 160,000 Chinese adults. Diabetes, 68(11), 2155–2164. Cited by 71.
5. Xu, Y., Chen, B., Qian, W., & Li, H. (2013). Properties of pure n-butylammonium nitrate ionic liquid and its binary mixtures with alcohols at T = 293.15 to 313.15 K. The Journal of Chemical Thermodynamics, 58, 449–459. Cited by 70.
Senior Research Fellow | Jomo Kenyatta University of Agriculture and Techno | Kenya
Dr. Amos Kipkorir Langat, Ph.D., is a highly accomplished statistician, academic, and economist with expertise in Bayesian analysis, machine learning, spatial statistics, and public health modeling. He earned his Ph.D. in Mathematics (Statistics) from the Pan African University Institute for Basic Sciences, Technology and Innovation, his MSc. in Applied Statistics from Jomo Kenyatta University of Agriculture and Technology (JKUAT), and his BSc. in Economics and Mathematics from Kabarak University. Currently, he serves as a Lecturer at JKUAT and Senior Economist at the County Government of Bomet, with previous teaching roles at Maasai Mara and Kabarak Universities. His research spans statistical modeling of infectious diseases, HIV risk factors, maternal health, survival and time series analysis, and measurement error models. He has supervised MSc. and Ph.D. students across Africa, authored over 30 peer-reviewed publications, and contributed to journals such as Scientific African, Asian Journal of Probability and Statistics, and Annals of Medicine & Surgery. Dr. Langat has secured prestigious awards including the AU Ph.D. Scholarship and SICSS research funding, and he actively contributes as a reviewer and conference organizer. His technical expertise includes proficiency in R, Python, STATA, SAS, SPSS, WinBUGS/OpenBUGS, and advanced econometric tools. A member of the Royal Statistical Society, ISCB, IBS, and the Kenya National Statistical Society, he also demonstrates a strong commitment to community service through educational leadership roles. Dr. Langat exemplifies a dedicated scholar, mentor, and researcher advancing applied statistics in public health and beyond
Profile: Google Scholar | Scopus | Orcid
Featured Publications
1. Langat, A., Orwa, G., & Koima, J. (2017). Cancer cases in Kenya; forecasting incidents using Box & Jenkins ARIMA model. Biomedical Statistics and Informatics, 2(2), 37–48. Cited by: 21
2. Benki-Nugent, S. F., Martopullo, I., Laboso, T., Tamasha, N., Wamalwa, D. C., … [and others]. (2019). High plasma soluble CD163 during infancy is a marker for neurocognitive outcomes in early-treated HIV-infected children. JAIDS Journal of Acquired Immune Deficiency Syndromes, 81(1), 102–109. Cited by: 14
3. Mutinda, J. K., & Langat, A. K. (2024). Stock price prediction using combined GARCH-AI models. Scientific African, 26, e02374. Cited by: 10
4. Mutinda, J. K., & Langat, A. K. (2024). Modeling the impact of air pollution and meteorological variables on COVID-19 transmission in Western Cape, South Africa. International Journal of Mathematics and Mathematical Sciences, 2024(1), 1591016. Cited by: 5
5. Mutinda, J. K., & Langat, A. K. (2024). Capital asset pricing model: A renewed application on S&P 500 index. Asian Journal of Economics, Business and Accounting, 24(6), 226–239. Cited by: 4