Research
Research
Research interests include artificial intelligence in education, agentic AI, responsible academic use of AI, analytics, intelligent systems, research practice, academic writing, and institutional readiness.
Research Agenda
My current research agenda is organized around the practical and institutional consequences of AI in academic work. I am interested in how AI changes teaching, assessment, research supervision, literature review, academic writing, publication practice, and the governance responsibilities of departments and institutions.
- Generative AI and Agentic AI in higher education
- Responsible AI use, academic integrity, and institutional policy
- AI-supported literature review, academic writing, and publication workflows
- Business analytics, forecasting, and decision support systems
- Explainable AI, intelligent systems, and applied emerging technologies
- Faculty development, assessment redesign, and departmental AI readiness
Current Questions
- How can faculty use AI while preserving reading, thinking, writing, and disciplinary judgment?
- What kinds of assessment remain meaningful when students have access to generative AI tools?
- How should research scholars document AI-supported literature review, writing, and analysis workflows?
- What should departments include in practical AI policy, disclosure, and governance documents?
- How will agentic AI affect academic administration, knowledge work, and research support?
- How can analytics and intelligent systems support institutional decision-making responsibly?
Current Direction
The emphasis is not on tool enthusiasm. The emphasis is on the academic conditions under which AI use becomes useful, accountable, verifiable, and educationally defensible. This includes human review, disclosure, privacy, source checking, assessment redesign, and careful distinction between assistance and authorship.
Research Approach
Most of the current work is applied and practice-oriented. It draws on classroom problems, research supervision needs, institutional policy discussions, faculty development requirements, and the practical difficulties faced by students and scholars when AI tools enter academic work.
- Conceptual frameworks that help faculty and institutions make decisions about AI use.
- Teaching and assessment designs that make learning evidence more visible.
- Research workflow guidance for literature review, writing, verification, and disclosure.
- Institutional readiness questions for departments, academic leaders, and policy committees.
Current Outputs
The research agenda is developed through books and edited volumes, academic notes, teaching materials, invited academic sessions, research scholar workshops, and collaboration-oriented writing. The aim is to produce material that can be read, discussed, adapted, and used in real academic settings.
- Guides on Generative AI, Agentic AI, responsible AI, and AI for research.
- Templates for disclosure, literature review, AI readiness, assessment redesign, and classroom policy.
- Session structures for FDPs, academic leaders, research scholars, and institutional committees.
- Book and publication work across AI, intelligent systems, education, analytics, and applied technology domains.
Selected Research Themes
Research Collaboration
Research collaboration inquiries may relate to co-authored papers, book chapters, edited volumes, research scholar development, institutional AI adoption studies, faculty development research, and research-oriented academic sessions.
A useful inquiry should briefly mention the proposed theme, institution or department context, expected output, timeline, and whether the collaboration is intended for a paper, chapter, edited volume, workshop, or institutional study.
- Suitable: focused papers, chapters, edited volumes, FDP-linked research outputs, and institutional AI readiness studies.
- Less suitable: very broad proposals without a research question, target output, timeline, or academic context.