Elvan Ceyhan
Member of The Honor Society of Phi Kappa Phi
From Auburn, AL
From Auburn, AL
Dr. Elvan Ceyhan is a professor of mathematics and statistics at Auburn University, where he holds the Marguerite Scharnagle Endowed Professorship. His work focuses on data science, graph-based machine learning, spatial statistics, and network optimization under uncertaintywith applications in public health, imaging, and education.
He earned his Ph.D. from Johns Hopkins University, where he also completed postdoctoral research. Prior to Auburn, he held academic positions at Ko University, the University of Pittsburgh, and North Carolina State University, including a leadership role as Deputy Director at SAMSI.
Dr. Ceyhan has published extensively, received national and international research awards, and serves on editorial boards of leading journals. A member of Phi Kappa Phi since 1999, he is also an elected member of the International Statistical Institute and a former Global Young Academy fellow.
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Elvan Ceyhan Receives 2024 Phi Kappa Phi Love of Learning Award
Elvan Ceyhan of Auburn, Alabama, was recently awarded a Love of Learning Award worth $1,000 from The Honor Society of Phi Kappa Phi, the nation's oldest and most selective collegiate honor society ...
October, 07 2024 - Verified by The Honor Society of Phi Kappa Phi
Elvan Ceyhan was recognized for graduating
Got PhD at Johns Hopkins University, Baltimore, MD 21218, USA. Applied Mathematics and Statistics. 2000 -
2005. Date of issuance: May 26, 2005. Advisor: Prof. Carey E. Priebe. Dissertation title: An Investigation
of Proximity Catch Digraphs in Delaunay Tessellations.
Added by Elvan
Elvan Ceyhan was recognized for graduating
Got MSE at Johns Hopkins University, Baltimore, MD 21218, USA. Statistics/ Mathematical Sciences. 2000 -
2002. Date of issuance: May 23, 2002.
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Elvan Ceyhan was recognized for graduating
Got MS at Oklahoma State University, Stillwater, OK 74078, USA. Statistics. 1998 - 2000. Date of issuance: July
28, 2000. Advisor: Dr. Carla L. Goad. Thesis title: A Comparison of Analysis of Covariance and ANOVA
Methods Using Covariate-Adjusted Residuals.
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Elvan Ceyhan was recognized for enrolling
Member, Phi Kappa Phi Honor Society, 1999 - Present.
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Elvan Ceyhan was recognized for earning an academic award
Phi Kappa Phi Love of Learning Award
Description:
Recipient of the competitive Love of Learning Award from the Honor Society of Phi Kappa Phi, which recognizes academic excellence and supports postdoctoral or professional development. The award funded ongoing research activities in graph-based statistical modeling and interdisciplinary applications of data science in education and public health. This honor reflects a sustained commitment to scholarly impact and lifelong learning.
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Professor at Auburn University
Teaching and research as Professor at the Department of Mathematics and Statistics, Auburn University, Auburn,
AL.
April 2024 - Present
Associate Professor at Auburn University
Teaching and research as Associate Professor at the Department of Mathematics and Statistics, Auburn
University, Auburn, AL.
July 2019 - April 2024
Research Associate Professor at North Carolina State University
Research Associate Professor at NCSU.
At the same time, I was also
Deputy Director of SAMSI (Statistical and Applied Mathematical Sciences
Institute), Durham, NC between 2017 August 16 2019 May 15.
July 2017 - May 2019
Visiting Associate Professor at University of Pittsburgh
Teaching
September 2016 - June 2017
Student Perspectives on AI in Education: A Survey and Reflection
This invited reflection explores student engagement with AI in the classroom, focusing on ethics, digital literacy, and responsible technology use. Featured in Auburn University’s AI in Teaching and Learning Showcase.
March 2025 -
Articles
Chair – ASA AL–MS Chapter Annual Conference and Business Meeting
Chaired the 2025 ASA Alabama–Mississippi Chapter Conference, hosted at Mississippi State University. Responsibilities included session coordination, awards, and engaging regional scholars in statistics and data science.
March 2025 -
Conferences
Compare Traditional Computational Results to AI-Enhanced Analysis
A reflection published by the Biggio Center at Auburn University as part of their 2025 AI in Teaching and Learning Showcase. The piece discusses pedagogical use of AI for enhancing statistical interpretation and critical thinking.
March 2025 -
Publications
Invited Talk – Optimizing Network Navigation in Stochastic Obstacle Scenes
Presented as part of an invited session at the 2024 INFORMS Annual Meeting, this talk explored probabilistic adversarial path planning and stochastic decision models.
Location: Seattle, WA
October 2024 -
Presentations
Co-Presenter – Future of Data Science: Education and Industry Alliances
Co-presented with Dr. Nedret Billor at Auburn University's Outreach and Engaged Scholarship Symposium on enhancing data science education through strategic partnerships.
Location: Auburn, AL
September 2024 -
Presentations
Invited Talk – Navigation Algorithms for Optimal Pathfinding in Stochastic Obstacle Scene Problem
Delivered an invited research talk at the 9th Workshop on Biostatistics and Bioinformatics, presenting new algorithms for graph-based traversal in uncertain environments.
Location: Georgia State University, Atlanta
May 2024 -
Presentations
AI Integration in Teaching Statistics and Data Science
Implemented AI-assisted tools into teaching workflows for computational statistics and Bayesian methods. Developed assignments, assessments, and class discussions focusing on ethical and responsible AI use in quantitative analysis.
January 2024 -
Classwork
pcds: Proximity Catch Digraphs and Their Applications
An R package providing tools for constructing and analyzing Proximity Catch Digraphs (PCDs), with applications in spatial pattern analysis, classification, and graph-based learning.
Role: Author & Maintainer
Platform: CRAN & GitHub
December 2023 -
Software Projects
pcds.ugraph: PCDs and Their Underlying/Reflexivity Graphs
Extends the functionality of pcds to include the construction and analysis of underlying and reflexivity graphs associated with PCDs. Useful for topological and network-based studies.
Role: Author & Maintainer
Platform: CRAN & GitHub
December 2023 -
Software Projects
nnspat: Nearest Neighbor Methods for Spatial Data Analysis
Implements nearest-neighbor-based statistical methods for analyzing spatial point patterns, including segregation and association tests.
Role: Author & Maintainer
Platform: CRAN & GitHub
December 2023 -
Software Projects
Stochastic Obstacle Scene Problem with Adversarial Agents
Principal Investigator on a National Science Foundation (NSF) funded project addressing decision-making in uncertain environments. The project develops optimization methods for pathfinding through stochastic networks, with applications in AI, robotics, and defense.
August 2023 -
Research Projects
Adversarial Risk Analysis for Optimal Obstacle Evasion
PI on an Office of Naval Research (ONR) project developing risk-aware decision frameworks for navigating adversarial environments. The research integrates probabilistic modeling, graph theory, and Bayesian inference.
August 2022 -
Research Projects
Graph-Theoretic Learning and Spatial Methods
Supported by a Simons Collaboration Grant, this project explores novel geometric digraph models for classification, clustering, and spatial data analysis.
September 2021 -
Research Projects
Design and Launch of Core Statistics Curriculum at Auburn University
Led the design and development of multiple new courses in the Department of Mathematics and Statistics at Auburn University to strengthen graduate and undergraduate training in modern statistical methods. Courses include:
STAT 7630: Bayesian Statistics (graduate)
STAT 4650: Introduction to Bayesian Statistics (undergraduate)
STAT 5610/6610 and 5620/6620: Fundamentals of Statistical Inference I & II
These courses integrate simulation-based inference, Bayesian modeling, and reproducible research practices, while emphasizing conceptual foundations and applications in data science.
August 2021 -
Classwork
Statistics & Data Science Seminar Series (Founder & Organizer)
Launched a departmental seminar series to foster interdisciplinary exchange among faculty and graduate students on cutting-edge topics in statistics, data science, and AI.
September 2020 -
Classwork
Classification Using Proximity Catch Digraphs
Introduces a novel family of graph-theoretic classifiers effective for imbalanced and high-dimensional datasets. Published in Machine Learning.
May 2020 -
Articles
PCDSL: Statistical Learning with Proximity Catch Digraphs
An R package under active development for statistical and machine learning methods that use Proximity Catch Digraphs, supporting classification, clustering, and outlier detection tasks.
Role: Author & Contributor
Platform: GitHub
March 2019 -
Software Projects
Classification of Imbalanced Data with a Geometric Digraph Family
Proposes a novel geometric graph-based classification method specifically designed to address challenges in imbalanced datasets. Published in the Journal of Machine Learning Research, a leading venue in the field.
October 2016 -
Articles
Session Co-Organizer – Graph Learning in High-Dimensional Data
Co-organized the invited session “Instance and Graph-Based Learning from High-Dimensional Data” at the International Conference on Information Complexity and Statistical Modeling (ICICSM), held in Cappadocia,
May 2016 -
Conferences
Segregation Indices for Disease Clustering
Proposes statistical measures for identifying and quantifying spatial disease clustering patterns. Published in Statistics in Medicine.
May 2014 -
Articles
Session Organizer – Graph-Theoretic Methods for Spatial Data
Organized the Special Topic Session 72 at the ISI World Statistics Congress, focusing on spatial data analysis using graph-theoretic methods.
August 2013 -
Conferences
Pattern Recognition in High-Dimensional Data (PRinHDD)
Funded through the Marie Curie International Outgoing Fellowship (EU-FP7), this project advanced geometric and topological methods for high-dimensional classification problems, including spatial and medical data contexts.
Funding Source: European Commission – Marie Curie IOF
August 2013 -
Research Projects
Optimal Obstacle Placement with Disambiguations
Presents optimization strategies for uncertain environments, addressing spatial planning challenges in network traversal problems. Published in Annals of Applied Statistics.
December 2012 -
Articles
Co-Chair – 8th World Congress in Probability and Statistics
Served as organizer and co-chair of this major international event bringing together researchers in probability and statistics. Coordinated sessions, logistics, and young researcher participation.
July 2012 -
Conferences
Extension of One-Dimensional Proximity Regions to Higher Dimensions
Generalizes classical proximity structures for spatial analysis to multidimensional settings. This article was also featured by VerticalNews (NewsRx).
November 2010 -
Articles
Proximity Catch Digraphs: Auxiliary Tools, Properties, and Applications
A technical monograph based on Dr. Ceyhan’s PhD dissertation, this book introduces a novel family of proximity-based graphs and explores their theoretical properties and applications in classification and spatial analysis.
ISBN: 978-3-639-19063-2
September 2009 -
Publications
Correcting for Covariates: Ratios, Residual Analysis, and ANCOVA
This volume, based on Dr. Ceyhan’s MS thesis, offers a detailed comparison of analytical approaches to adjusting for covariates in experimental design, with practical implications in applied statistics.
ISBN: 978-3-639-19607-8
September 2009 -
Publications
Organizer and Chair – Spatial Statistics in Epidemiology (ISI Congress)
Organized and chaired the invited session “Spatial Statistics in Epidemiology” at the ISI Congress in Durban, contributing to global discussions on statistical methods in public health.
August 2009 -
Conferences
