GIS Specialist · ML Engineer · Remote Sensing

TILAK KUMAR

S H
Mapping the Earth. Training the Machines.

I fuse geospatial intelligence with AI to build systems that understand our planet — from early warning systems for landslides, to predictive flood maps, to Mars rover terrain navigation.

// LOCATION51.9607° N7.6261° E // DOMAINGIS · ML · RSBCA Graduate // STATUSOpen to Work
Scroll
10+
Projects Shipped
6+
Certifications
4+
GIS Platforms
C2
English Proficiency

Where data meets the physical world

I'm a BCA graduate from Surana College, Bangalore, now based in Münster, Germany — with a deep specialisation in GIS, remote sensing, and machine learning. My work sits at the intersection of geospatial technology and AI.

I've built AI systems for landslide early warning, deep learning navigation for Mars rovers, full-stack geospatial platforms for NYC crash analysis, and carbon mapping tools for the Sundarbans — all the way from raw satellite data to deployed web applications.

I'm driven by impact: using Earth observation data and machine learning to tackle real crises in environmental monitoring, urban planning, and disaster response.

Python · TensorFlow · Scikit-learn95%
ArcGIS · QGIS · Remote Sensing92%
Machine Learning · Deep Learning90%
SQL · PostGIS · Data Analysis88%
Google Earth Engine · MODIS · SAR85%
Flask · FastAPI · Streamlit82%
Docker · AWS · MLOps · Git75%
Work Experience

Where I've contributed

Mar – Apr 2024
Bangalore, IN
Machine Learning Intern
Syslog Technologies · Bangalore
Worked on computer vision projects — developing and fine-tuning models for visual data using Python, OpenCV, and TensorFlow. Built end-to-end ML workflows from data preprocessing through model training, hyperparameter tuning, and deployment. Collaborated with data scientists to deliver production-ready solutions via Flask and FastAPI.
Scikit-learnTensorFlowKerasOpenCVFlaskFastAPI
Selected Projects

Systems I've built

02
Geospatial · ML · Full-Stack
NYC Accident Risk Intelligence
Full-stack geospatial system analysing NYC crash data with PostGIS spatial queries, hotspot detection, and ML severity-risk predictor (LOW/MEDIUM/HIGH). Flask REST API with 9 endpoints, Mapbox UI with 24-hour animation and real-time user report submission.
PostGISFlaskScikit-learnMapbox GL JSPostgreSQL
03
GIS · Web App · Logistics
NYC Truck Routing Platform
Web-based navigation platform generating truck-specific optimised routes across NYC, accounting for vehicle dimensions and local regulations. Integrates Google Maps API for real-time guidance and Stripe for payment processing.
Node.jsExpress.jsGoogle Maps APIStripeGIS
04
Remote Sensing · Google Earth Engine
Land Cover Change Detection
Detects and quantifies land cover change between 2001–2020 using MODIS MCD12Q1 in Google Earth Engine. Binary change maps, area calculations in km², and cloud-optimised GeoTIFF export at 30m resolution across 17 land cover classes.
Google Earth EngineMODISJavaScriptGeoTIFF
05
Climate · Remote Sensing · Carbon
Coastal Blue Carbon Mapping — Sundarbans
Maps coastal vegetation and estimates carbon stock in the Sundarbans using Sentinel-2 and MODIS in Google Earth Engine. Calculates NDVI, classifies vegetation, and performs historical change detection for blue carbon sequestration analysis.
Sentinel-2MODIS NDVIGoogle Earth EngineCarbon Stock
06
Renewable Energy · GEE · Spatial Analysis
Solar Suitability Score
Computes a composite solar suitability score using MODIS and Landsat in GEE. Analyses NDVI, land cover, terrain slope, and solar radiation to identify optimal zones for solar energy installation.
Google Earth EngineLandsatMODISSolar Radiation
07
Climate · ML · Data Visualisation
Hurricane Wind Speed Prediction
Tracks hurricane routes and predicts wind speed from barometric pressure using linear regression on NOAA Atlantic hurricane data. Interactive path visualisation with Folium and Plotly.
PythonScikit-learnFoliumPlotlyNOAA
08
AI · Disaster Management · Philippines
AI Early Warning System for Landslides
As Data Analysis Lead, built an AI-driven landslide risk prediction system for disaster-prone regions of the Philippines. Led preprocessing, feature engineering, and model training. Integrated with disaster management frameworks for real-time alerts.
Machine LearningPythonGISReal-time Alerts
09
Agriculture · Climate · ML
Rainfall Prediction Model
ML model predicting seasonal rainfall patterns from historical weather data. Regression algorithms identify key meteorological drivers — supporting agricultural planning and water resource management.
RegressionPythonPandasMatplotlib
10
Remote Sensing · LiDAR · DEMs
Terrain Analysis for LiDAR Flight Optimisation
Analysed Digital Elevation Models to compute optimal flight altitudes and swath widths for LiDAR data capture over varied topography — enhancing accuracy and cost-efficiency of environmental and infrastructure surveys.
DEMsJupyterLiDARPython
Education & Certifications

Where I've learned

Bachelor's Degree
Bachelor of Computer Applications (BCA)
Surana College · Bangalore University
2021 – 2024
NASA Certification
Drought Monitoring, Prediction & Projection
NASA ARSET
Aug – Sep 2024
ESA / EO College
Winter-Water-Warming: Canadian SAR Applications
EO College
Jul – Aug 2024
Certification
Deep Learning Object Classification in ArcGIS Pro
Esri
2024
Certification
Machine Learning for Earth Observation
Online
2024
Certification
Spatial Data Science with Earth Engine
Google / GEE
2024
Certification
Cloud Computing with AWS
Amazon Web Services
2024
Certification
Advanced Python Programming
Online
2023

Ready to build something remarkable?

Open to full-time roles, research collaborations, and freelance projects in GIS, ML, and remote sensing. Based in Münster, Germany — available globally.