Savannah L. Kelly is Associate Head and Associate Professor in the Scholar Support and Data Services (SSDS) Department at the University Libraries of the University of Mississippi. She plays a key role in advancing data and statistical literacy among students, faculty, and librarians through research, instruction, and collaboration. Her educational background includes a PhD in Higher Education with an Interdisciplinary Minor in Applied Statistics, a Master of Library and Information Science, and a Bachelor of Science in Psychology with a minor in Philosophy. Dr. Kelly's research focuses on promoting data science and statistical competencies in higher education, interdisciplinary research collaborations, and understanding students’ perceptions of STEM majors and careers. She is passionate about improving quantitative research skills and supporting learners through innovative pedagogical approaches. Her recent publications and presentations highlight a strong trend in statistical education, research data services, information literacy, and academic librarianship. She emphasizes accessible data science training, the use of tools like R and Zotero, and the importance of aligning library services with student needs. IRDL Scholar (2016) IRDL Mentor (2018–2020) ACRL Immersion Program (Teacher Track, 2010; Assessment Track, 2012) Excellence in Assessment Award, Westmont College (2012) People’s Choice Award, EBLIP 2017 Dr. Kelly actively mentors students and collaborates across disciplines. She has led workshops and developed programming such as an R workshop series for graduate students. Her work is supported by professional development grants and institutional programs like IRDL. She is a Certified Instructor for The Carpentries, reflecting her commitment to open, reproducible research practices. She contributes to library-led research through projects on student research challenges, faculty-librarian collaboration, and service loads in academic librarianship. Her work helps shape library instruction, research support services, and data science initiatives at the institutional and national levels.








