
Christopher Kinson
Academic · Statistics Education
University of Illinois Urbana-ChampaignAbout
Christopher Kinson is a Teaching Associate Professor in the Department of Statistics at the University of Illinois at Urbana-Champaign. He holds a Ph.D. from the same institution, advised by Prof. Annie Qu, and previously served as a Visiting Assistant Professor. His research focuses on statistics and data science education, emphasizing reproducible programming methods and pedagogical innovation. Kinson teaches courses like STAT 385 (Statistics Programming Methods) and STAT 440, integrating R, Git, and version control into curriculum design. He was awarded the NSF Graduate Research Fellowship in 2012 and has contributed to educational outreach through advising roles in the department's Master’s Program (2018–2020). His teaching philosophy emphasizes critical thinking, collaborative learning, and accessible computational tools.
Education:
- Ph.D. in Statistics, University of Illinois (2017), advised by Prof. Annie Qu
- M.S. in Statistics, University of Illinois (2015)
- B.S. in Mathematics, Albany State University (2011), Velma F. Grant Honors Scholar
Research & Teaching Interests: Kinson specializes in developing reproducible statistical workflows, open educational resources, and inclusive teaching practices. He designs curricula that bridge theoretical concepts with practical coding skills using R and version control systems. His initiatives promote computational literacy among undergraduate and graduate students through hands-on programming projects and collaborative learning environments.
Awards & Recognition:
- NSF Graduate Research Fellowship (2012)
- Promoted to Teaching Associate Professor (2023)
Academic Service: Served as academic advisor for the department’s Master’s Program (2018–2020). Actively contributes to course development, including STAT 385’s online asynchronous format and GitHub-integrated learning platforms.
Labs/Teams: Leads the department’s educational technology initiatives, focusing on integrating modern tools like RMarkdown and Git into statistics education.
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