Research

My research sits at the intersection of machine learning and its practical applications — particularly in contexts where data is scarce, infrastructure is limited, and the stakes for getting it right are high.

Research Domains

Scientific Machine Learning

Physics-informed neural networks, simulation surrogates, and data-driven approaches to modeling physical systems. Interested in how ML can accelerate engineering simulation without sacrificing interpretability.

Computer Vision

Image understanding, document digitization (OCR/ICR for Devanagari script), and photogrammetric reconstruction. Earlier work includes UAV-based 3D reconstruction of heritage sites and terrain mapping.

AI for Education

Curriculum design for AI education, intelligent tutoring systems, and the challenge of building AI literacy at scale in emerging markets. Ongoing research interest growing from a decade of building AI programs in Nepal.

Publications

Publications list coming soon. In the meantime, see my ORCID profile for the current list.

In Progress

Current work focuses on AI for Education — specifically, designing adaptive learning systems for AI curricula in resource-constrained environments.

Collaboration

Open to research collaboration, particularly on projects that combine ML methods with real-world deployment challenges in Nepal and the broader South Asian context. Get in touch →