Su Chen, PhD

• 2013, PhD in Statistics, Oklahoma State University
• 2012, Master in Quantitative Financial Economics, Oklahoma State University
• 2009, Master in Statistics, Oklahoma State University
• 2007, BS in Statistics, Wuhan University of Technology

Dr. Chen's research interests mainly focuses on non-/semi-parametric statistical modeling and data analysis on large-scale human genetics & epigenetics, as well as intelligent tutoring/learning data. Dr. Chen also served as a statistical consultant to help with statistical planning/design, power calculation, and data analysis over the past 10 years.

• Chen, S., Fang, Y., Shi, G., Sabatini, J., Greenberg, D., Frijters, J. and Graesser, A. (2021). Automated Disengagement Track- ing Within an Intelligent Tutoring System. Frontiers in Artifi- cial Intelligence, section AI for Human Learning and Behavior Change. doi: 10.3389/frai.2020.595627. 

• Chen, S. (2020) Generalized expected value of continuous random variables and its applications. Communications in Statistics: Theory and Methods, DOI: 10.1080/03610926.2020.1725823 

• Chen, S. (2020) A new distribution-free k-sample test: Analysis of kernel density functionals, The Canadian Journal of Statis- tics, 48(2): 167-186. 

• Chen, S., Refaey, H., Mukherjee, N., Solatikia, F., Jiang, Y., Arshad, H., Ewart, S., Holloway, J., Zhang, H., Karmaus, W. (2020) Ages at onset of different pubertal signs in boys and girls and differential DNA methylation at age 10 and 18 years: an epigenome-wide follow-up study, Human Reproduction Open, doi: 10.1093/hropen/hoaa006.
• Chen, S. and Pokojovy, M. (2018) Modern and classical k-sample omnibus tests, Wiley Interdisciplinary Reviews: Computational Statistics , 10(1), e1418:112.

• American Statistical Association (ASA)
• Institute of Mathematical Statistics (IMS)

• International Chinese Statistical Association (ICSA)
• International Biometrics Society, Eastern North American Region (ENAR)