Building next-generation Earth Observation systems, AI-driven geospatial platforms, GeoAI agents & skills, and cloud-native solutions that bridge space technology with real-world impact.
I'm Dr. Kazi Rifat Ahmed, a Full Stack Geospatial AI Engineer & Tech Lead specializing in transforming how industries leverage Earth Observation data through cutting-edge technology, satellite data services, innovation, and leadership.
Advanced machine learning and deep learning solutions for satellite imagery analysis and geospatial intelligence.
Scalable, resilient geospatial platforms using Kubernetes, microservices, and modern DevOps practices.
Large-scale EO data processing, analytics, and visualization from multi-sensor platforms.
Blockchain and Quantum Computing applications for next-generation geospatial solutions.
The first affordable multi-sensor drone that sees through anything. Combines X-band Synthetic Aperture Radar with RGB, near-infrared, thermal, and LiDAR — all co-registered on a single platform with onboard edge AI.
AI-driven decision-support platform generating go/no-go confidence scores for road running, trail running, road biking, and mountain biking by analyzing location-based weather forecasts with ML. Features natural-language route creation, interactive editing, GPX/KML export for Garmin, interactive web maps, and an LLM chatbot.
ML/DL-powered web app forecasting Bitcoin, Ethereum, and XRP prices across daily to weekly horizons by fusing historical market data, social media sentiment, and trading volumes. Includes an interactive dashboard and an integrated LLM chatbot (Llama 3.2 via Ollama) for conversational analysis of blockchain trends.
Blockchain-based food traceability service supporting local farmers with direct-to-customer sales, food ordering & delivery, live tracking, crypto payments, food security & quality certification, farmer-customer networking, and an interactive web dashboard with regional farm details and web map. Developed at Swiss Blockchain Hackathon 2019.
Real-time weather and astronomical data app showing 5-day forecasts, full sun ephemeris (sunrise/sunset, golden hour, solar noon, day length), moon ephemeris (phase, illumination, moonrise/moonset), illustrated moon phases, and interactive web maps with sun/moon positions and daylight terminator line.
Query geospatial data with natural language and visualize on map and chart with custom styles — replacing complex traditional GIS software for data query and visualization. Easily download results without handling multiple complex software.
Specially trained LLMs for coding geospatial tasks with detailed explanations and downloadable code files (Python, Java, C/C++, Rust, JavaScript). Architecture based on the GeoAI-Assistance-Ext project.
A VS Code extension for local GeoAI assistance on any geospatial task with an integrated chat interface powered by DeepSeek-R1 via Ollama.
Combination of unsupervised and supervised machine learning algorithms for satellite image classification to produce precise location-based landuse/landcover maps. Useful for the wider GeoAI community.
Jupyter notebooks for calculating widely used optical indices from satellite images — for studying earth surface features and their spatio-temporal changes.
QuantumED UG, Darmstadt, Germany
Sensor Aktor GmbH, Darmstadt, Germany
Remote Sensing Laboratory, University of Zurich, Switzerland
Spacenus GmbH, Darmstadt, Germany
ISEE Bangladesh, Vanderbilt University, USA
Swiss Blockchain Hackathon
Developed SOMO (SOil to MOuth), an innovative blockchain solution for the agriculture and food sector using Amazon Managed Blockchain with Hyperledger Fabric.
View Winning PitchImageCLEF 2017
Best performing team for population density estimation using Copernicus Sentinel-2 data and machine learning algorithms.
ESA Land Remote Sensing Course
Awarded at the 8th Advanced Training Course on Land Remote Sensing, University of Leicester, organized by ESA.
German Academic Exchange Service
Fully funded academic scholarship for M.Sc. at TU Darmstadt, including thesis funding for geoscience research.
Thesis: Remote Sensing of Sun-Induced Chlorophyll Fluorescence for Advanced Ecosystem Evapotranspiration Estimates
Top 5% of class • Major in Remote Sensing & Geoinformatics
Ranked 2nd • Major in Remote Sensing & Geomorphology
Major in Geoinformatics, Remote Sensing & Hydrogeology
Interested in collaboration, research opportunities, or satellite data services?
Explore my ventures: