Nedret Billor, PhD

Nedret Billor, PhD

  • Professor, Interim Chair
  • Mathematics and Statistics
  • The Deans Office
    • 334-844-3619
    billone@auburn.edu
    1178 STEM-Ag, Building A
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    Nedret Billor is a Professor of Statistics and the Interim Chair of the Department of Mathematics and Statistics at Auburn University. She has been leading the expansion of data science education and research across campus. Over the past several years, she helped develop the MS in Data Science and Engineering, established the new PhD in Statistics and Data Science, and created strong industry-based capstone experiences for students.

    Her research interests center on robust statistical methods, outlier and anomaly detection, functional and multivariate data analysis, and statistical machine learning, with applications in environmental and earth system sciences. She enjoys building collaborations across disciplines and working with partners in academia, industry, and government. She is also passionate about advancing data literacy and creating opportunities that connect students, researchers, and communities through data science.

    Education

    • PhD in Statistics Sheffield University 1992

    • MSc in Statistics Cukurova University 1985

    • BSc in Mathematics Ankara University 1983

    Professional Experience

    Co-Director, Center for Data Science and Innovation (CDSI)
    Auburn University
    2024–2026

    • Built interdisciplinary research and educational initiatives in data science.
    • Developed collaborations with industry, government and academic partners.
    • Promoted data literacy and data-driven innovation across campus.

    Architect, M.S. in Data Science and Engineering Program
    Auburn University
    2019–2026

    • Led the design and approval of Auburn’s first data science degree.
    • Established an industry-sponsored capstone model that remains in use.

    Lead Developer, Ph.D. in Statistics and Data Science
    Auburn University
    Approved 2024

    • Designed the curriculum and successfully guided the program through approval.
    • Supported program launch and student recruitment.

    Innovation

    My research develops robust statistical methodologies for complex and high-dimensional data structures, with a focus on outlier and anomaly detection, robust estimation, and robust learning. I work on multivariate and functional data analysis, including functional classification, distance-based methods, and robust dimension-reduction techniques. My work often addresses challenges arising from non-normality, heavy tails, measurement noise, and atypical observations that can mislead classical procedures. I am particularly interested in methodological frameworks that achieve robustness without sacrificing efficiency and that provide theoretical guarantees for inference and prediction. Current projects include robust functional classifiers based on Gaussian processes, methods for high-dimensional anomaly detection, and application-driven approaches for environmental and earth system datasets. A substantial component of my research involves adapting modern statistical learning techniques to real data conditions, with emphasis on interpretability, uncertainty quantification, and performance in the presence of contamination

    Engagement

    I am committed to expanding data literacy and creating opportunities for students and communities to engage with data science. My outreach work includes developing industry capstone projects, building statewide partnerships, and promoting data-driven education through the Center for Data Science and Innovation.

    Leadership & Program Development

    I have been actively involved in developing and expanding data science education and research at Auburn University. Over the past several years, I helped establish the MS in Data Science and Engineering, created the PhD in Statistics and Data Science, and strengthened our graduate programs through new curricula, interdisciplinary activities, and student recruitment. In my role as Interim Chair, I continue to support faculty, staff, and students, and promote a collaborative environment that advances both disciplinary excellence and campus-wide engagement in data science.

    Center for Data Science and Innovation (CDSI)2 Title

    I served as Co-Director of the Center for Data Science and Innovation, a new interdisciplinary initiative bringing together faculty, students, industry partners, and community organizations to advance data science and AI across campus. The Center focuses on research, education, and engagement, with activities that include working groups, seminar series, collaborative projects, and partnerships with external stakeholders. Our goal is to build a sustainable hub that supports innovation and provides real-world impact in areas such as agriculture, climate, health, and community development.

    Industry Partnerships

    A key component of my work has been developing long-term partnerships with industry organizations and national laboratories. These collaborations have created capstone projects, research opportunities, publications and career connections for our students.

    I have worked with partners across a range of sectors, including engineering, energy, finance, power systems, national laboratories and international organizations, to create meaningful applied-learning experiences and bring industry expertise into our academic programs. I continue to expand these partnerships to connect students with emerging opportunities and strengthen Auburn’s presence within the broader data science ecosystem.