Academic inquiry & applied innovation

Research & Publications

Advancing the foundations of intelligent systems through rigorous inquiry, open research, and a commitment to AI that remains reliable, interpretable, and useful.

Fields of inquiry

Research Interests

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01

AI in Pedagogy & Education

Investigating the role of AI in personalized learning, curriculum design, and the development of intelligent tutoring systems. Have build AI enabled education platform with multiple types of graders with feedback for code, subjective, objective, image and video graders. Have AI-enabled proctoring platform that flags suspicious activities during online exams. Content Authoring Tool to generate contents, questions and answers for multiple choice, subjective, objective questions, supporting mathematics and coding with variations of context, phrasing and scenarios.

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Scientific Machine Learning

Developing physics-informed neural networks and data-driven discovery of governing equations for complex systems.

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Agentic AI

Exploring the design of autonomous agents capable of reasoning, planning, and acting in complex environments.

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Computer Vision & Pattern Recognition

Investigating hierarchical feature extraction in multi-modal environments and the robustness of spatial understanding in synthetic datasets.

05

Natural Language Processing

Semantic drift analysis and long-context retrieval mechanisms within transformer-based architectures.

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Reliable & Alignment-First AI

Making AI systems explainable, predictable, and consistently aligned with human intent across diverse cultural contexts.

Collaboration Inquiries

Interested in academic partnership or technical consulting for AI reliability? My door is open for substantive research dialogues.

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