Research Portfolio
My research explores the intersection of AI-mediated inquiry, recursive methodologies, and qualitative research frameworks. Currently pursuing publication in leading academic journals, my work investigates how AI can serve as a collaborative partner in research and creative processes.
Current Publications Under Review
Recursive Cognition in Practice
Status: Under peer review at the International Journal of Qualitative Methods
Abstract: This article introduces Recursive Cognition in Practice (RCIP) as a structured, AI-mediated dialogue method. It demonstrates how AI can serve simultaneously as co-writer, co-theorist, and co-analyst — recursively producing both knowledge and its own methodology in real time. The work challenges conventional epistemology and authorship norms, providing a theoretical and methodological foundation for AI-assisted scholarship.
Key Contributions:
- Novel methodological framework for AI-human collaboration in research
- Theoretical foundation for recursive cognition as scholarly practice
- Practical implementation of co-authorship with AI systems
- Epistemological implications of human-AI knowledge co-construction
Author ORCID: 0009-0000-0363-5229
Conversations With AI: Exploring Dialectical Tension Through Autoethnography and AI-Mediated Reflection
Status: Under peer review at The Journal of Autoethnography
Abstract: This article presents an AI-mediated autoethnographic study that investigates the dialectical tension between autonomy and connection within recursive human-AI dialogue. Drawing on lived experience and structured conversational loops with an AI model, the author examines how reflexivity, emotional regulation, and narrative identity are shaped through iterative interaction. Rather than treating AI as a neutral analytic tool, the work positions it as a co-regulator, provocateur, and mirror—revealing the entangled dynamics of self, machine, and meaning-making. The piece challenges traditional boundaries of authorship, authenticity, and emotional methodology in post-qualitative research.
Key Contributions:
- Introduces recursive AI dialogue as an emotionally reflexive mode of autoethnographic inquiry
- Theorizes dialectical tension (autonomy vs. connection) through lived recursive interaction
- Frames AI not as a collaborator or object, but as a generative site of affective and epistemic tension
- Demonstrates methodological potential for AI in emotion-centric, post-qualitative autoethnography
Author ORCID: 0009-0000-0363-5229
Research Interests
- AI-mediated qualitative research methodologies
- Recursive cognition and reflexive inquiry
- Human–AI co-authorship in knowledge production
- Post-qualitative and affect-driven research frameworks
- Epistemological and ontological implications of AI dialogue
- Mixed methods approaches to recursive, AI-assisted inquiry
🧠 Statement of Purpose
My research aims to legitimize and advance AI-assisted scholarship by developing rigorous, recursive methodologies that foreground emotional reflexivity, epistemic entanglement, and methodological innovation. I'm particularly interested in how AI-mediated dialogue challenges traditional assumptions about authorship, agency, and the production of knowledge—ultimately reimagining research as a co-constructed, dynamic process.