Ranjidha Rajan

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Ranjidha Rajan

Assistant Professor of Computer Sciences

Computer Sciences

Office Hours

Fall 2026 Office Hours - In-person/MS Teams
M/W - 9 AM to 11 AM
M- 4 PM to 5 PM

Biography

Assistant Professor of Computer Science at Metropolitan State University of Denver. Her research interests include AI in Education, Graph Data, and visualization, with a focus on applying emerging technologies to computing education and interdisciplinary research.

Research Interests

    My research interests focus on Artificial Intelligence in Education, graph analytics, data visualization, and computing education. I explore how AI, network-based methods, and visual analytics can help people understand complex data, identify meaningful relationships, and make informed decisions. My research includes using generative AI to support inquiry and data literacy, as well as graph analytics and visualization to understand educational, organizational, and workforce ecosystems. I am particularly interested in applied, interdisciplinary research that connects technological innovation with real-world educational and societal challenges.

Teaching Interests

    My teaching philosophy centers on creating an inclusive, inquiry-driven, and applied learning environment where students develop the confidence to explore, question, and solve meaningful problems. I emphasize connecting foundational computer science concepts with real-world applications through hands-on projects, data-driven inquiry, collaborative learning, and responsible use of emerging technologies such as generative AI. Across courses in computer science and AI, I encourage students to move beyond learning tools and techniques to understanding how and why they should be applied. My goal is to help students become thoughtful problem solvers who can apply their technical knowledge to complex challenges.

Education

EdD in Learning Analytics

National University

Other in Data Analysis

IIIT Bangalore,India

MS in Computer Science

Bharathiar University Coimbatore

BS in Physics

M G University

Personal Website

https://www.linkedin.com/in/dr-ranjidha-rajan-488548b0/

Published Works

    Geinitz, S., Rajan, R., Peprah, K., Schmidt, C. K., Singh, S., Jay, M. S. (2026). Generative AI as a Tool for Learning: Higher Education Student Perceptions and Performance Across Disciplines. (pp 3-14). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-25387-3_1 Rajan, R. (). Scaffolding Data Literacy Through AI-Augmented Inquiry: The 5E Data Questioning Cycle. The Journal of Computing Sciences in Colleges, http://dl.acm.org/.”. Kim, Y., Rajan, R. (2026). Explainability Analysis of Retrieval-Driven Behavior in RAG Pipelines.. , https://doi.org/10.5281/zenodo.18945160 Geinitz, R. S., Rajan, R., Peprah, K., Schmidt, C. K., Singh, S., Jay, M. S. (). Generative AI as a Tool for Learning: Higher Education Student Perceptions and Performance across Disciplines. Springer. Rajan, R., C, R. (2024). Ethical Integration in Computer Science Education: Leveraging Open Educational Resources and Generative Artificial Intelligence for Enhanced Learning.. IEEE/PPIG. Rajan, R. (2023). The pragmatism of evolving social presence in online discussion forums. ProQuest Dissertations & Theses A&I. McKinney, L., Sinley, C. R., Daughtrey, C., Ansburg, P., Rajan, R., Meyer, J., Lopez, R. J., Eaker, L. R. (2021). Faculty Are Our Allies in Teaching Career Preparation and Readiness Skills. National Association of Colleges and Employers Journal, www.naceweb.org Ansburg, P., Daughtrey, C., Eaker, L. R., Lopez, R. J., McKinney, L., Meyer, J., Rajan, R., Sinley, C. R. (2021, April (2nd Quarter/Spring)). Who should teach career preparation and career readiness skills?. Marketing Educators' Association Conference Proceedings 2021. Arundhathi, B., Athira, A., Rajan, R. (2017). A Study on Mutual Information-Based Feature Selection in Classifiers. (pp 479-486). Springer Singapore. https://doi.org/10.1007/978-981-10-3174-8_40 Rajan, R. . A study on Mutual Information-based Feature Selection in Classifiers. . Springer Publications, Rajan, R. (2017). An extensive study on data thinning in single and ensemble classifiers. International Journal of Pure and Applied Mathematics, Academic Publications.