Publications & Research

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Researching how people interact with intelligent systems.

I am a PhD researcher in Human-Centered Computing at Clemson University. My work spans human-AI interaction, AI-supported learning, accessible computing, explainable AI, and reliable data systems.

My current work explores how people reason and learn with intelligent technologies, and how AI-generated information can become useful, inspectable interfaces. My published research brings perspectives from human-machine interaction, accessibility, privacy, and distributed systems to these questions.

Questions and systems in progress

Current research

The research questions and applications I am developing now.

Ongoing doctoral research

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AI-supported mathematical reasoning

Exploring how AI assistance may influence mathematical reasoning, cognitive engagement, and independent problem-solving in interactive variant Sudoku environments.

Human-AI Interaction
Learning Sciences
Research Design

Explore the research

Active research application

Quizzibility

AI-assisted classroom interaction

My engineering contributions focus on instructor-facing interfaces for inspectable AI analysis of student responses, alongside infrastructure supporting controlled research conditions.

UX Engineering
Human-AI Interaction
Educational Technology

Explore my engineering contribution

Published research

Selected publications

A closer look at three publications representing my work in human-machine interaction, accessibility, and reliable data systems.

2026

Qualitative interview study

Soldiers' perspectives on natural user interfaces in combat vehicle operations

Christopher Lawson, Md Atik Enam, Ethan Butler, Raphael Ugboko, Dustin J. Souders, Jerome McClendon & Julian Brinkley

Behaviour & Information TechnologyPublished online 24 September 2026 · pp. 1–39

Research focus: Exploratory semi-structured interviews with 13 participants examined how operational constraints and environmental conditions shape interaction with combat vehicles. The study found that suitable interface modalities depend on mission context, task demands, and multimodal design.
Why it matters: Interface choices need to account for real operating conditions rather than assume an ideal interaction environment.

Read publication View case study Human-Computer Interaction · Natural User Interfaces

2024

Preliminary design guidelines

Accessible Autonomous Vehicles as Symbiotic Autonomous Systems for Users with Disabilities: Preliminary Design Guidelines

Julian Brinkley & Raphael Ugboko

2024 IEEE 4th International Conference on Human-Machine Systems (ICHMS)Conference paper · pp. 1–5

Research focus: Considers how accessibility and the needs of people with disabilities can inform preliminary design guidance for autonomous mobility systems.
Why it matters: Advanced autonomous systems need interaction designs that account for diverse abilities and access requirements.

Read publication View case study Accessibility · Human-Machine Interaction

2026

Simulation-based comparison

Resilient geospatial data management: a comparative analysis of cloud-native and distributed ledger technology synchronization models for multi-cloud environments

Oluwafemi Oloruntoba, Princewill Odum, Khadijah Audu, Sheriff Adepoju, Raphael Ugboko & Oluwabukola Racheal Tiamiyu

Journal of Cloud Computing15(1), Article 87 · Published 12 June 2026

Research focus: Uses simulation-based analysis to compare cloud-native and distributed-ledger synchronization under failure scenarios. The comparison examines trade-offs among performance, resilience, data integrity, and operational cost.
Why it matters: Reliable data systems require explicit trade-offs between speed, consistency, auditability, and operational complexity. These findings concern the simulated conditions.

Read publication Distributed Systems · Data Reliability

Complete bibliography

All publications

7 publications, grouped by research direction.

Human-Centered AI, Interaction & Accessibility

2026

Soldiers' perspectives on natural user interfaces in combat vehicle operations

Christopher Lawson, Md Atik Enam, Ethan Butler, Raphael Ugboko, Dustin J. Souders, Jerome McClendon & Julian Brinkley

Behaviour & Information Technology · Published online 24 September 2026 · pp. 1–39

Qualitative interview study

Read paper

2024

Accessible Autonomous Vehicles as Symbiotic Autonomous Systems for Users with Disabilities: Preliminary Design Guidelines

Julian Brinkley & Raphael Ugboko

2024 IEEE 4th International Conference on Human-Machine Systems (ICHMS) · Conference paper · pp. 1–5

Preliminary design guidelines

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2025

Explainable Artificial Intelligence in Autonomous Vehicles: Methodologies, Challenges, and Prospective Directions

Raphael Ugboko & Oluwafemi Oloruntoba

Iconic Research and Engineering Journals · 8(10), pp. 1578–1593

Review and taxonomy

Reviews explainability approaches, including post-hoc methods and interpretable models, alongside trust, safety, and real-time constraints.

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AI, Privacy & Reliable Data Systems

2026

Resilient geospatial data management: a comparative analysis of cloud-native and distributed ledger technology synchronization models for multi-cloud environments

Oluwafemi Oloruntoba, Princewill Odum, Khadijah Audu, Sheriff Adepoju, Raphael Ugboko & Oluwabukola Racheal Tiamiyu

Journal of Cloud Computing · 15(1), Article 87 · Published 12 June 2026

Simulation-based comparison

Read paper

2025

Optimizing Data Pipelines for Real-Time Healthcare Analytics in Distributed Systems: Architectural Strategies, Performance Trade-offs, and Emerging Paradigms

Olasehinde Omolayo, Raphael Ugboko, Deborah Olamide Oyeyemi, Oluwafemi Oloruntoba & Samuel O. Fakunle

International Journal of Scientific and Management Research · 8(7), pp. 89–99

Synthetic-data benchmarking

Compares pipeline architectures using synthetic healthcare data and performance benchmarks, examining latency, throughput, scalability, and operational cost.

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2025