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About

The story behind the pixels.

Why I traded topographic sheets for tensors, and what I'm working toward.

Portrait of Santosh Chapagain

Profile

  • Nationality
    Nepali
  • Location
    Pokhara, Gandaki Province, Nepal
  • Languages
    Nepali, English
  • Interests
    Anime & visual storytelling, cybersecurity awareness, open-source mapping
  • Hobbies
    Trail photography, sketching contour maps, competitive Kaggle notebooks

Biography

I'm a fourth-semester Geomatics Engineering student at the Institute of Engineering, Paschimanchal Campus (Tribhuvan University), Nepal. My work lives at the intersection of satellite imagery, geographic information systems, and machine learning — using each to answer a simple question: what is actually happening on the ground, and how do we know sooner?

Growing up in a country shaped by monsoon floods, earthquakes, and retreating glaciers, I became interested early in how remote sensing could turn distant, delayed information into something local communities could act on immediately. That interest has since grown into a structured research direction spanning crop monitoring, disaster response, and climate risk mapping.

Research Vision

I want to build GeoAI systems that are both scientifically rigorous and genuinely usable — models that don't just perform well on benchmark datasets, but that hold up against the messiness of real satellite revisit gaps, cloud cover, and data-scarce regions like the Himalaya. My long-term goal is a fully funded PhD in Geospatial AI, followed by a research career applying Earth observation and deep learning to climate adaptation in South Asia.

Professional Values

Rigor

Reproducible pipelines, honest cross-validation, no shortcuts on ground-truth.

Local Relevance

Models grounded in Nepal's terrain, seasons, and data realities — not generic benchmarks.

Openness

Sharing code, datasets, and dashboards freely wherever possible.

Personal Timeline

How I got here

2022

Started B.E. in Geomatics Engineering

Enrolled at IOE Paschimanchal Campus, Tribhuvan University, drawn to the blend of surveying, GIS, and spatial computation.

2023

First GIS & Remote Sensing Coursework

Discovered Google Earth Engine and Python-based geospatial analysis; began self-teaching machine learning fundamentals.

2024

First Applied ML Projects

Built early prediction pipelines (house price modeling, dataset engineering) to strengthen ML fundamentals.

2025

GeoAI Focus Solidifies

Began NDVI-based crop yield prediction research and started scoping a GeoAI venture concept for South Asian agriculture.

2026 →

Scholarship & PhD Track

Preparing applications for Erasmus Mundus Copernicus, DAAD, and ITC Orange Knowledge programs while building a research portfolio.