Research
Research
My research focuses on the application of mathematical modeling and machine learning to systems analysis, optimization, and data-driven decision-making. My work bridges the gap between theoretical frameworks and real-world challenges in finance, insurance, and structural analysis.
My interests extend to advanced probabilistic modeling, particularly in leveraging machine learning algorithms to enhance predictive accuracy in risk assessment and decision-making. With a background in applied mathematics and actuarial science, I explore novel methodologies to improve efficiency and reliability in areas such as claims processing, underwriting, and portfolio optimization.
I am particularly drawn to the intersection of optimization and machine learning, seeking innovative ways to develop adaptable models that can address diverse challenges in dynamic systems. My research also includes a focus on data analysis and statistical modeling, key tools for understanding complex patterns and behaviors in systems.
Selected Publications
Antimicrobial Resistance and Tuberculosis Prevalence in Africa: A Public Health Concern
with Adewale Adeboye Adewole and Jesseline Mwinila Eledi
Iconic Research And Engineering Journals, 2024
News
I Was Nominated to Join Phi Kappa Phi Honor Society
I was nominated for membership in the Virginia Commonwealth University (VCU) chapter of The Honor Society of Phi Kappa Phi, the nation’s oldest and most selective all-discipline honor society.
Membership is by invitation only and is extended to VCU’s top 10 percent of seniors and graduate students, recognizing outstanding academic achievement across all fields of study.
I’m grateful for this recognition and honored to be considered among a distinguished community of scholars committed to excellence, service, and meaningful contribution.
I Joined a Panel Discussion at the MARMA Conference
I was invited to participate in a panel discussion at this year’s Mid-Atlantic Regional Math Alliance (MARMA) Conference, hosted by Howard University, on the topic: “The Rise and Use of AI in STEM Education and Research: Pros and Cons.”
The discussion explored how artificial intelligence is shaping STEM teaching, learning, and research, including its potential to improve access, support innovation, and enhance productivity, while also raising important questions around ethics, academic integrity, equity, and responsible use.
I’m grateful for the opportunity to contribute to such a timely conversation alongside other scholars and educators committed to the future of STEM.
I Presented My Research at the INFORMS 2025 Annual Meeting
I presented my poster, “Microbiome-Aided Classification of Forensic Body Fluids via Conjecturing and Machine Learning,” at the INFORMS 2025 Minority Issues Forum (MIF) Poster Competition during the Annual Meeting.
The research integrates interpretable machine learning with microbial signatures to advance forensic analysis. I'm grateful to my advisor, Dr. Paul Brooks, and collaborators.
I also gave a talk on Reinforcement Learning alongside colleagues (Sahil Chindal, Parastoo B., Mauli Pant, Rekik Ziku, and Godfred Ahenkroa Kesse), sharing new findings and future directions.
I Completed the Ohio University Young Alumni Leaders Program
I have completed the Ohio University Young Alumni Leaders Program as part of the Fall 2025 cohort.
This program, hosted by the Ohio University Alumni Association, brought together emerging alumni leaders for intentional learning, mentorship, and community-building around values-driven leadership and service. It has deepened my commitment to leading with integrity, amplifying the impact of fellow Bobcats, and giving back to the communities that shaped me.
I’m grateful to the Alumni Association team, our facilitators, and my cohort peers for the insights, encouragement, and friendships built along the way.
I Delivered a Graduate Seminar at VCU
On April 29, 2025, I delivered a graduate seminar at Virginia Commonwealth University (VCU) on my research titled “Heuristics to Learning: A Reinforcement Approach to Mathematical Conjecturing.”
My presentation introduced a novel reinforcement learning (RL) method for automating symbolic reasoning tasks by integrating RL into mathematical conjecturing frameworks. Building on the deterministic Dalmatian heuristic used in the CONJECTURING tool by Brooks et al., I proposed a dynamic RL-based approach that filters and evaluates symbolic expressions through sequential decision-making.
The seminar was well received by faculty and graduate students, highlighting new directions for automated reasoning in mathematics.
Me with Member in a Minute | 2024 INFORMS Annual Meeting
The 2024 INFORMS Annual Meeting was held in Seattle, Washington, from October 20–23, 2024, at the Seattle Convention Center.
It brought together 6,000+ professionals in operations research, analytics, data science, and management science to exchange ideas, present research, and network with peers from academia, industry, and government. The meeting featured keynote sessions, technical tracks, tutorials, and opportunities for collaboration across disciplines.