INSIGHT Lab
Interdisciplinary Network for Science, Intelligence, Growth, Health & Technology
Turning data into insight. Turning insight into impact.
The INSIGHT Lab is an emerging interdisciplinary research initiative focused on advancing human-centered applications of data science, artificial intelligence, health analytics, education, and advanced quantitative methods.
Our Mission
The mission of the INSIGHT Lab is to advance interdisciplinary research that connects data, artificial intelligence, and quantitative methods with meaningful human and societal challenges.
The lab seeks to:
- Conduct rigorous and impactful interdisciplinary research
- Advance responsible and human-centered applications of artificial intelligence
- Develop reproducible and transparent research workflows
- Support doctoral students and emerging researchers
- Promote collaboration across disciplines, institutions, and sectors
- Translate analytical findings into actionable knowledge
- Create opportunities for students to participate in research, publication, and scholarly dissemination
Research Pillars
Artificial Intelligence & Intelligent Systems
Research on predictive AI, generative AI, agentic AI, retrieval-augmented generation, human–AI collaboration, trust, explainability, responsible AI, and AI-supported decision-making.
Learning & Education Analytics
Research on AI literacy, learning analytics, student engagement, academic success, technology-enhanced learning, and responsible AI use in education.
Health & Wellness Analytics
Research applying data science and advanced analytics to sleep, physical activity, psychological wellness, population health, epidemiology, and health informatics.
Methods, Evidence & Open Science
Research advancing structural equation modeling, Bayesian methods, meta-analysis, bibliometrics, predictive modeling, reproducibility, and open science.
Current and Emerging Research Directions
The INSIGHT Lab is designed to support a portfolio of interconnected research projects rather than a single narrow research agenda.
Current and emerging areas of interest include:
Human–AI Decision-Making
Examining how individuals and organizations interact with artificial intelligence when making decisions, including questions related to trust, explainability, uncertainty, accountability, and decision quality.
AI Attitudes and Adoption
Investigating the individual, psychological, organizational, and contextual factors that shape attitudes toward artificial intelligence and influence AI adoption.
Retrieval-Augmented Generation and Emerging AI
Studying the evolution, research landscape, applications, and methodological development of retrieval-augmented generation and other emerging AI systems.
Health and Wellness Analytics
Using public health and population datasets to investigate relationships among sleep, physical activity, psychological wellness, metabolic risk, and other health outcomes.
Reproducible Bibliometric Research
Developing transparent and reusable workflows that integrate tools such as OpenAlex, R, Bibliometrix, VOSviewer, and computational text analysis.
Research Synthesis and Meta-Analysis
Synthesizing evidence across studies to better understand complex relationships in artificial intelligence, education, health, and organizational research.
Doctoral Research and Mentorship
A central goal of the INSIGHT Lab is to create opportunities for doctoral students and emerging scholars to develop as independent researchers.
Students affiliated with the lab may have opportunities to participate in:
- Research design and theory development
- Literature reviews and evidence synthesis
- Data collection and secondary data analysis
- Advanced statistical modeling
- Machine learning and AI research
- Bibliometric and meta-analytic studies
- Reproducible research workflows
- Conference presentations
- Manuscript development
- Open science and research dissemination
The lab will encourage doctoral researchers to move beyond completing individual studies toward developing broader programs of scholarship.
Learn More About Doctoral Mentorship →
A Reproducible Research Philosophy
The INSIGHT Lab is committed to research practices that make scholarship more transparent, reliable, and reusable.
Where appropriate, projects will emphasize:
- Pre-registration of research questions and analytical plans
- Transparent documentation of research decisions
- Version control using Git and GitHub
- Reproducible analytical workflows
- Open-source statistical tools
- Public code repositories
- Open Science Framework project documentation
- Clear reporting of methods and limitations
- Responsible and transparent use of artificial intelligence
Research workflows may incorporate tools such as R, Python, Quarto, GitHub, JASP, Jamovi, Stata, SAS, Power BI, OpenAlex, Bibliometrix, and VOSviewer, depending on the needs of each project.
Collaboration
Complex problems rarely belong to a single discipline.
The INSIGHT Lab is envisioned as a collaborative environment that brings together researchers with interests in:
- Data science
- Artificial intelligence
- Computer science
- Education
- Health and wellness
- Public health
- Business and organizational research
- Learning analytics
- Quantitative methodology
- Research synthesis
Future collaborations may include faculty researchers, doctoral students, graduate students, industry professionals, healthcare researchers, educational institutions, and international research partners.
Opportunities for Students
One of the long-term goals of the INSIGHT Lab is to create meaningful pathways for students to participate in research.
Doctoral Researchers
Developing dissertation research while participating in broader research programs and collaborative scholarship.
Graduate Research Assistants
Supporting data analysis, literature synthesis, research programming, and scholarly dissemination.
Student Research Collaborators
Contributing to faculty-led or interdisciplinary projects with opportunities for conference presentations and publications.
Independent Research Projects
Developing open-source analytical projects that demonstrate advanced research and data science skills.
As the lab develops, specific opportunities and active projects will be posted here.
Research Outputs
INSIGHT Lab research will aim to contribute through multiple forms of scholarly and public impact, including:
- Peer-reviewed journal articles
- Conference presentations
- Open-source analytical workflows
- Public datasets and code
- Research tutorials
- Evidence syntheses
- Bibliometric studies
- Meta-analyses
- Research software and tools
- Student-led scholarship
Building the Lab
The INSIGHT Lab represents a long-term vision for building an interdisciplinary research community around data, artificial intelligence, and human-centered inquiry.
As the initiative grows, this page will evolve to include:
- Lab members
- Doctoral researchers
- Student research assistants
- Faculty collaborators
- External research partners
- Active projects
- Publications
- Research resources
- Open positions and collaboration opportunities
The goal is to build a research environment where methodological rigor, intellectual curiosity, collaboration, and mentorship come together.
Interested in Collaborating?
I welcome opportunities to connect with researchers, doctoral students, and collaborators whose interests intersect with the mission of the INSIGHT Lab.
Potential areas for collaboration include artificial intelligence, data science, health analytics, education, research synthesis, quantitative methodology, and reproducible research.