I am a geospatial scientist and researcher focusing on hydroclimatology, satellite precipitation calibration, and environmental dynamics. Currently finalizing my MPhil thesis with plans to transition into doctoral research, my work bridges academic inquiry and applied environmental consultancy. I specialize in utilizing Google Earth Engine, Python, and machine learning models to correct global climate datasets for regional accuracy in Southeast Asia.
I develop workflows that automate heavy spatial data processing. In the spirit of open science, base methodologies are open-source. For enterprise application, commercial licensing is available.
An automated pipeline that extracts historical climate data (ERA5-Land, CHIRPS) and calibrates it against local ground-truth data using machine learning bias correction. Designed to output standardized SPI metrics for corporate TCFD reporting and hydrological risk assessments.
Evaluating and correcting satellite precipitation estimates for drought monitoring across tropical catchments. This research informs my forthcoming master's thesis and lays the groundwork for my future PhD methodologies.
Developed sub-pixel water contour extraction scripts (MNDWI) using Sentinel-2 composites. This reduces the manual digitization bottleneck in generating Environmental Sensitivity Index (ESI) reports for high-priority terminal sites.
Writings on the intersection of geospatial science, data processing, and environmental policy.