Dr. Itauma Itauma
Data Scientist · Professor · Researcher · Academic Leader
Associate Professor of Data Science and Analytics
Harrisburg University of Science and Technology
I study how data, artificial intelligence, and advanced analytical methods can be used to generate better evidence, support better decisions, and improve outcomes across education, health, and human-centered systems.
Research Areas
AI, Data Science & Education
Understanding how artificial intelligence and data science shape learning, decision-making, human behavior, and educational outcomes.
Focus areas: AI literacy · Predictive AI · Generative AI · Human–AI collaboration · Learning analytics
Health & Wellness Analytics
Using data and advanced analytics to investigate health behaviors, population health, and wellness outcomes.
Focus areas: Sleep · Physical activity · Metabolic health · Psychological wellness · Health informatics
Advanced Quantitative Methods
Applying rigorous statistical and computational approaches to complex research questions.
Focus areas: SEM · Bayesian statistics · Machine learning · Meta-analysis · Predictive modeling
Science of Research & Emerging AI
Studying how knowledge is created, synthesized, reproduced, and transformed by emerging AI technologies.
Focus areas: Bibliometrics · Open science · Reproducibility · RAG · Agentic AI
INSIGHT Lab
Interdisciplinary Network for Science, Intelligence, Growth, Health & Technology
Turning data into insight. Turning insight into impact.
The emerging INSIGHT Lab brings together research in artificial intelligence, data science, education, health analytics, and advanced quantitative methods.
The vision is to create a collaborative research community where faculty, doctoral students, graduate researchers, and external partners can pursue rigorous, reproducible, and human-centered scholarship.
Teaching & Doctoral Mentorship
ANLY 735 – Research Seminar in Predictive AI
A research-centered seminar exploring current developments in machine learning and predictive artificial intelligence, with emphasis on scholarly literature, critical evaluation, research communication, and emerging technologies.
ANLY 799 – Doctoral Studies
Doctoral research mentorship focused on helping emerging scholars develop theoretically grounded, methodologically rigorous, reproducible, and impactful research.
Featured Research
Artificial Intelligence
Human–AI Decision-Making
Examining how trust, explainability, uncertainty, accountability, and human oversight shape decision quality in AI-supported environments.
Health Analytics
Sleep & Metabolic Health
Investigating how sleep quality, sleep duration, physical activity, and related behaviors contribute to metabolic and population health outcomes.
Research Methods
Reproducible Research Workflows
Developing transparent workflows for bibliometrics, meta-analysis, evidence synthesis, and computational research.
About My Work
My scholarship spans artificial intelligence, data science, education and learning analytics, health and wellness analytics, and advanced quantitative methods. I am particularly interested in research that connects rigorous analytical methods with meaningful human, educational, organizational, and health outcomes.
I also mentor doctoral researchers and emerging scholars in developing research that is theoretically grounded, methodologically sound, reproducible, and positioned to make a practical contribution.