Research

Co-Mentor | UNC Greensboro Computational Statistics Research Experience for Undergraduates (REU) 2025

• Research area: Complex Data Analysis Using Statistical And Machine Learning Tools. (NSF Grant DMS-2244160)

• Department of Mathematics and Statistics | Research Experience for Undergraduates (REU)

• Working with Dr. Thomas Weighill.

Poster Session Judge | Carolyn & Norwood Thomas Undergraduate Research and Creativity Expo 2025

• Content Area: STEM

• Organizers: UNC Greenaboro' Undergraduate Research, Scholarship & Creativity Office (URSCO)

North Carolina Agricultural & Technical State University | The Math Scholar's Institute - Academic Recovery Summer Program

• Ezugwu, Chidinma. "Unlocking Your Math Potential: Embracing Your Learning Style." Workshop presented at the Math Scholars Institute, North Carolina A&T State University, Summer 2024.

• Ezugwu, Chidinma. "Decoding Complex Problems: Analytical Skills Bootcamp." Workshop presented at the Math Scholars Institute, North Carolina A&T State University, Summer 2024.

• Ezugwu, Chidinma. "Mastering Math Study Skills: Techniques for Effective Learning and Retention." Workshop presented at the Math Scholars Institute, North Carolina A&T State University, Summer 2024.

• Ezugwu, Chidinma. "Mastering Math: Advanced Study Techniques for Complex Concepts." Workshop presented at the Math Scholars Institute, North Carolina A&T State University, Summer 2024.

North Carolina Agricultural & Technical State University | Aggie Success Academy S.I.S.T.E.R.S. - Female Students Mentorship Program in Mathematics

• Ezugwu, Chidinma. "Math Unveiled: Unlocking the Power of Numbers in Your Future." Workshop presented at the Aggie Success Academy Residential Pre-College Summer Program, North Carolina A&T State University, Summer 2024. 

• Ezugwu, Chidinma. "Math Empowerment: Transforming Mindsets, Accelerating Skills." Workshop presented at the Aggie Success Academy Residential Pre-College Summer Program, North Carolina A&T State University, Summer 2024.

• Ezugwu, Chidinma. "Math Fundamentals: Learning FUN-damentals." Workshop presented at the Aggie Success Academy Residential Pre-College Summer Program, North Carolina A&T State University, Summer 2024.

• Ezugwu, Chidinma. "Math Refresher: Mastering Linear Inequalities in Two Variables." Workshop presented at the Aggie Success Academy Residential Pre-College Summer Program, North Carolina A&T State University, Summer 2024.

• Ezugwu, Chidinma. "Math Refresher II: Navigating Quadratic Functions." Workshop presented at the Aggie Success Academy Residential Pre-College Summer Program, North Carolina A&T State University, Summer 2024.

NC A&T Center for Academic Excellence | S.I.S.T.E.R.S Summer of Success 

NorthEast Regional Computing Program (NERCOMP) and EDUCAUSE Annual Conference 2025, Rhode Island, USA

Ezugwu, Chidinma. "Innovative Instructional Methods for Diverse Learners in a Post-Pandemic World: Adaptive Socio-Spatial Learning." Presented at the NERCOMP Annual Conference 2025. Graduate Teaching Associate, Department of Mathematics and Statistics, University of North Carolina at Greensboro

Session Abstract Poster

EDUCAUSE and NERCOMP Annual Conference 2025 

Ezugwu, C. (2025). Innovative Instructional Methods for Diverse Learners in a Post-Pandemic World. Presented at the EDUCAUSE and NERCOMP Annual Conference 2025 , Providence, Rhode Island.

Link to Session Abstract.

UNCG Mathematics and Statistics | Graduate Research Seminar 

Ezugwu, C. (2025). Diffusion Distance and Permutations for Spatial Autocorrelation Analysis. Presented at the Mathematics and Statistics Graduate Research Seminar, Greensboro, North Carolina.

19th Annual Regional Mathematics and Statistics Conference 

Ezugwu, C. (2023). Diffusion Distance and Permutations for Spatial Autocorrelation Analysis. Presented at the 21st Annual Regional Mathematics and Statistics Conference, Greensboro, North Carolina.

Funded by the National Science Foundation Grant no. DMS-2324883.

19th Annual Regional Mathematics and Statistics Conference 

Ezugwu, C. (2023). Reducing the Number of Node Expansions by DIBBS. Presented at the 19th Annual Regional Mathematics and Statistics Conference, Greensboro, North Carolina.

National Science Foundation Grant no. DMS-2324883.

Institute for Partners in Education & GCS Tutors Conference 

Ezugwu, C. (2023). Momentous Little Efforts: Going the Extra Mile as a Tutor. Presented at The Inaugural Annual Tutoring Conference | Guilford County Schools & Institute for Partners in Education (Tutoring Collaborative), Greensboro, North Carolina.

• C. Ezugwu, " Reducing the number of node expansions by DIBBS,” M.S. thesis, Department of Mathematics and Statistics, Southern Illinois University, Edwardsville, IL, 2021. Paper Link 

• Ezugwu, Chidinma. (2017). Stagflation in Nigeria: A New Theory and Case Study. 10.13140/RG.2.2.23147.31528. Paper Link 

Ezugwu, C. C. (2024, Nov 24). Emerging Trends in Retail Credit and Spending [LinkedIn post]. LinkedIn. Article link 

Ezugwu, C. C. (2021, May 20). A Voyage for the Light [LinkedIn post]. LinkedIn. Article link 

“Aggie Rocketry 2025 NASA Student Launch Computational Analysis” 

Analyzed IMU data to accurately model rocket velocity in three dimensions, achieving close alignment between predicted and actual velocities. Optimized the velocity prediction algorithm using linear acceleration data. Spring 2025.

Member of North Carolina Agricultural & Technical State University "Aggie Rocketry" Team, NASA Student Launch Challenge 2024-2025.

"Customer Churn Predicton" - Solving Problems with Data Analysis

High-level analysis of customer churn prediction using machine learning (ML) modeling techniques.

"Enhancing MRI Classification through Optimal Thresholding in Machine Learning" - Big Data and Machine Learning

This study investigates advanced methodologies for the classification of brain MRI scans, employing sophisticated image processing techniques and machine learning algorithms to differentiate between neoplastic and non-neoplastic cases. While previous research has focused on minimizing the F1 score for threshold selection, this approach may negatively impact other performance metrics. To address this, the study evaluates various thresholding methods to enhance overall model performance. Additionally, it incorporates principal component analysis (PCA) to create new feature spaces from the original data, allowing for a comprehensive exploration of informative features. By improving thresholding strategies and utilizing PCA, the study offers deeper insights into model performance and enhancing the accuracy of brain tumor predictions using machine learning algorithms.

“Performance Evaluation of Resampling Methods in Claims Reserving” - Statistical Computing Project at UNC Greensboro

In this paper, we evaluate the performance of prominent resampling methods in claims reserving. This graduate study focused on resampling Pearson residuals obtained from fitting a quasi-Poisson model to loss data and utilized the predicted future losses in computing future reserves. Via numerical analysis, we determine the more effective resampling methods based on computed prediction errors and other pertinent metrics. 

“Reducing the Number of Node Expansions by DIBBS” - Southern illinois University Masters Thesis

This paper discovers and proves various interesting and useful properties of a new Bidirectional Heuristic Search (BHS) algorithm that dynamically improves the bounds during its execution. The algorithm, Dynamically Improved Bounds Bidirectional Search (DIBBS), has the property that it always terminates on or before the forward search meets the backward search. It also has the ability to solve certain problems while expanding fewer nodes than prominent BHS algorithms like GBFHS and MMe. Ultimately, we present a theorem that can be used in reducing the number of nodes expanded by DIBBS in solving a shortest path problem.  SIUE, Spring 2021.

Collaboratively Solved the Institute of Industrial Engineers and Rockwell Automation’s Third Annual Contest Problem 3

This work is a collaborative project with colleagues in the Advanced Simulation Modeling course at SIUE. Using ARENA Event Simulation software, we model, analyze, and solve –with remarkable results—the Institute of Industrial Engineers and Rockwell Automation’s Third Annual Contest Problem 3: Sally Model’s SM Pizza Shop. SIUE, Fall 2019.

“Cognitive Learning Preferences” at Castleton University Applied Statistics

This project (supervised by Dr. A. Rajia) used IBM SPSS to identify the cognitive learning preferences of Castleton University Applied Statistics students.

Market Research for Student Recruitment at Castleton University

Integrated Marketing and Communications Practicum, Mathematics Department.

“Economic Development Research” at The Chamber & Economic Development of the Rutland Region

This research work analyzes census and provincial data of Rutland County, Vermont to detect trends and inform decision-making for regional improvement. 

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With Love.

Link to The SFH 

God bless you.