AI Climate Modeling
Advanced predictive workflows for rainfall forecasting, streamflow response, meteorological drought, reference evapotranspiration, and climate variability.
Expertise & Applied Capabilities
Technical strengths in climate, water, and agriculture research.
High-performance scientific computing and domain engineering honed through environmental data science, hydrology, remote sensing, and agricultural systems.
Environmental Intelligence
Data cleaning, QA/QC protocols, Sen's slope trend detection, statistical modeling, interactive visualization, and interpretation of nonstationary time series.
Research Writing & Review
High-impact scientific manuscripts, state-of-the-art literature reviews, reproducible methods documentation, peer reviews for top journals, and technical reports.
GIS & Remote Sensing AI
QGIS spatial modeling, Land Use / Land Cover (LULC) prediction, river-basin spatial regionalization, and satellite data fusion (GRACE, MODIS, ERA5).
Smart Agriculture
Crop water requirement computation, smart greenhouse irrigation circulation, soil moisture dynamics, and climate-smart agricultural adaptation.
Training & Technical Mentoring
Extensive experience teaching Python, PyTorch/TensorFlow, hydrological modeling, research methodology, and AI application workshops.
Selected Implementations
Applied R&D systems and case studies
Real-world deployments bridging machine learning theory and water management practice.
Seasonal Rainfall Forecasting with WaveNet-LSTM
A hybrid deep learning architecture designed to capture both high-frequency precipitation pulses and seasonal monsoon persistence for water-basin planning.
Climate Variability & Crop-Yield Risk Mapping
A geospatial graph neural network (GNN) framework combining spatial neighbor matrices and meteorological anomalies for rainfed agricultural risk assessment.
K-WaterGuard AI Monitoring Dashboard
An automated Python and Web GIS operational system translating open water-quality data into real-time hazard classification, maps, and stakeholder alerts.