Jiefei Wang, PhD

Jiefei Wang, PhD
Assistant Professor
Department of Biostatistics & Data Science

Physical address:
UHC, Suite 4.538
1005 Harborside Drive
Galveston, TX

Mailing address:
301 University Boulevard
Galveston, TX 77555-1150

Phone: (409) 772-2515
Email: jiewang@utmb.edu

Dr. Jiefei Wang is an Assistant Professor in the Department of Biostatistics & Data Science at the University of Texas Medical Branch (UTMB). He specializes in biostatistics with a focus on the development of novel statistical methods and translational research. His research interests include high-dimensional data analysis, Machine learning algorithms, and Natural language processing. Dr. Wang is actively involved in providing statistical support services to UTMB faculty, staff, and students, and he teaches graduate-level biostatistics courses.

Dr. Wang earned his Ph.D. and M.A. in Biostatistics from the University at Buffalo, SUNY, and a B.A. in Mathematics and Applied Mathematics from Shenzhen University, Guangdong, China. His professional experience includes working with the Bioconductor Core Team at Roswell Park Comprehensive Cancer Center, where he developed R packages for high-performance computing and software for scalable cloud storage and computing.

Dr. Wang’s research has led to significant contributions in statistical methodology and its applications in biomedical research. He has published extensively in peer-reviewed journals and presented his work at national and international conferences. He is also involved in various grant-funded projects, including those supported by the National Institute of Child Health and Human Development and the Cancer Prevention and Research Institute of Texas.
- PhD, Biostatistics, University at Buffalo, 2022
- MA, Biostatistics, University at Buffalo, 2018
- BA, Mathematics and Applied Mathematics, Shenzhen University, 2015
[1] Kseniya S Masterova, Jiefei Wang, Courtney Mack, Tatiana Moro, Rachel Deer, and Elena Volpi. “ Enhancing Flow Mediated Dilation Analysis by Optimizing an Open-Source Software with Automated Edge Detection”. In: Journal of Applied Physiology (2024).
[2] Jeffrey C Miecznikowski and Jiefei Wang. “ Error control in tree structured hypothesis testing”. In: Wiley Interdisciplinary Reviews: Computational Statistics 15.4 (2023), e1603.
[3] Jeffrey C Miecznikowski and Jiefei Wang. “ Exceedance control of the false discovery proportion via high precision inversion method of Berk-Jones statistics”. In: Computational Statistics & Data Analysis 185 (2023), p. 107758.
[4] Daniel Puebla Neira, Mohammed Zaidan, Shawn Nishi, Alexander Duarte, Christopher Lau, Sairam Parthasarathy, Jiefei Wang, Yong-Fang Kuo, and Gulshan Sharma. “ Healthcare Utilization in Patients with Chronic Obstructive Pulmonary Disease Discharged from Coronavirus 2019 Hospitalization”. In: International Journal of Chronic Obstructive Pulmonary Disease (2023), pp. 1827–1835.
[5] Merina Thomas, James Flaherty, Jiefei Wang, Morgan Henderson, Vivian Ho, Mark Cuban, and Peter Cram. “ Comparison of hospital online price and telephone price for shoppable services”. In: JAMA Internal Medicine 183.11 (2023), pp. 1214–1220.
[6] Jiefei Wang and Jeffrey C Miecznikowski. “ High precision implementation of Steck’s recursion method for use in goodness-of-fit tests”. In: Journal of Applied Statistics 49.6 (2022), pp. 1348–1363.
[7] John Reza Matthews, Jiefei Wang, Jiwei Zhao, Melissa A Kluczynski, and Leslie J Bisson. “ The influence of suture materials on the biomechanical behavior of suture-meniscal specimens: a comparative study in a porcine model”. In: Knee Surgery & Related Research 32 (2020), pp. 1–8.
[8] Hakeem J Shakir, Justin M Cappuzzo, Hussain Shallwani, Amanda Kwasnicki, Carli Bullis, Jiefei Wang, Ryan M Hess, and Elad I Levy. “ Relationship of grit and resilience to burnout among US neurosurgery residents”. In: World Neurosurgery 134 (2020), e224–e236.
[9] Hamidreza Rajabzadeh-Oghaz, Jiefei Wang, Nicole Varble, S-I Sugiyama, Ayako Shimizu, Linkai Jing, Jian Liu, Xinjian Yang, Adnan H Siddiqui, Jason M Davies, et al. “ Novel models for identification of the ruptured aneurysm in patients with subarachnoid hemorrhage with multiple aneurysms”. In: American Journal of Neuroradiology 40.11 (2019), pp. 1939–1946.
[10] LaVerne W Thompson, Kathryn D Bass, Justice O Agyei, Elizabeth Borngraber, Jiefei Wang, Renée M Reynolds, et al. “ Incidence of nonaccidental head trauma in infants: a call to revisit prevention strategies”. In: Journal of Neurosurgery: Pediatrics 24.6 (2019), pp. 689–696.
[11] Basel M Touban, Sonja Pavlesen, Jason B Smoak, Michael J Sayegh, Jiefei Wang, Jiwei Zhao, and Mark J Anders. “ Decreased lean psoas cross-sectional area is associated with increased 1-year all-cause mortality in male elderly orthopaedic trauma patients”. In: Journal of orthopaedic trauma 33.1 (2019), e1–e7.
[12] Joshua E Meyers, Jiefei Wang, Asham Khan, Jason M Davies, and John Pollina. “ Trends in physician reimbursement for spinal procedures since 2010”. In: Spine 43.15 (2018), pp. 1074–1079.
[13] Hakeem J Shakir, Matthew J McPheeters, Hussain Shallwani, Joseph E Pittari, and Renée M Reynolds. “ The prevalence of burnout among US neurosurgery residents”. In: Neurosurgery 83.3 (2018), pp. 582–590.
[14] LaVerne W Thompson, Kathryn Bass, Justice Agyei, Naseem Hibbit-Ur-Rauf, Jiefei Wang, and Renee Reynolds. Rising incidence of non-accidental trauma in infants: a call to revisit prevention strategies. 2018.
[15] Jun Zhang, Jiefei Wang, Cuizhen Niu, and Ming Sun. “ Quantile regression estimation for distortion measurement error data”. In: Communications in Statistics-Theory and Methods 47.20 (2018), pp. 5107–5126.
[16] Jeffrey C Miecznikowski, Jiefei Wang, Daniel P Gaile, and David L Tritchler. “ A novel exact method for significance of higher criticism via Steck’s determinant”. In: Statistics & Probability Letters 130 (2017), pp. 105–110.
[17] Nicole Varble, H Rajabzadeh-Oghaz, Jiefei Wang, Adnan Siddiqui, Hui Meng, and Ashkan Mowla. “ Differences in morphologic and hemodynamic characteristics for “PHASES-based” intracranial aneurysm locations”. In: American Journal of Neuroradiology 38.11 (2017), pp. 2105–2110.
[18] Jiefei Wang, Yupeng Chen, Tao Li, Jian Lu, and Lixin Shen. “ A Residual-Based Kernel Regression Method for Image Denoising”. In: Mathematical Problems in Engineering 2016.1 (2016), p. 5245948.

Jiefei Wang, PhDAssistant ProfessorDepartment of Biostatistics & Data Science

Jiefei Wang, PhD
Assistant Professor
Department of Biostatistics & Data Science