I am an AI engineer and geophysicist specializing in computational geoscience and autonomous data systems. I build platforms that ingest planetary-scale data - from real-time disaster APIs to satellite imagery - and transform it into actionable intelligence. My background ranges from 3D subsurface geomodelling to developing self-learning scrapers and deployment-ready climate monitoring architectures.
A real-time global disaster intelligence platform entirely powered by open government APIs. It dynamically aggregates and normalizes data from USGS Earthquakes, NASA EONET Wildfires, NOAA Weather Alerts, and NASA FIRMS Satellite Fire Detection into a single unified stream. Features a built-in GeoScience AI Assistant to help developers and scientists map disaster impacts using remote sensing.
4 Gov APIs UnifiedMulti-source normalizer pipeline for global coverage
Server-Sent Events (SSE)Real-time push engine without polling delays
A web scraper that teaches itself. Point it at any website - it figures out the structure,
extracts data using LLMs, and remembers what worked. Next time it hits the same domain,
it's faster and more accurate. It builds domain-specific profiles, scores its own output quality,
and auto-evolves its extraction prompts. Headless Chrome under the hood, with persistent memory
that compounds over time.
Self-Evolving PromptsGets smarter with every single scrape
Persistent MemoryDomain profiling that compounds over time
Born out of frustration with Berlin's brutal housing market. This bot crawls 50+ real estate
portals worldwide, applies your exact filters - price, rooms, location, commute time - and
fires matching listings to your Telegram 24/7. It uses an LLM-powered universal crawler
that adapts to any portal's layout. Now features a Live Demo on Hugging Face to try
the real-time scraping pipeline directly from your browser.
50+ PortalsGlobal coverage, not just one platform
Instant Telegram AlertsNew listings hit your phone in seconds
Live HF DemoReal-time scraping execution in browser
A Critical Review of Participatory Approaches in Water Management for Climate Change Adaptation
My primary contribution to the field of Global Change Geography is the Conditional Enabling Framework (KIEA), developed to diagnose and evaluate participatory water governance under severe climate stress and hydrological non-stationarity.
Traditional models assume participation uniformly yields positive outcomes - my research demonstrates that participation often devolves into tokenism or elite capture unless four interdependent enabling conditions are met simultaneously: Knowledge Performance (K), Institutional Performance (I), Equity Performance (E), and Adaptive Performance (A).
Figure: The KIEA Dimensions & Binding Constraint Logic.
Through a realist synthesis of 121 global water management studies, this diagnostic instrument directly shifts theoretical climate governance toward measurable, actionable, and prescriptive implementation.
A detailed geomodelling case study on the Teapot Dome, demonstrating advanced workflows in 3D subsurface modeling and reservoir characterization. Published in the highly respected Journal of Applied Geophysics.
My first career was interpreting what's beneath your feet - 3D seismic surveys, subsurface
geological models, wellbore data. I earned a BSc in Geophysics from Bahria University
(3.55/4.00 CGPA) and placed 3rd in the Imperial Barrel Awards, Asia Pacific - one of
the most competitive geoscience competitions organized by the AAPG.
Then I moved to Berlin for an MSc in Global Change Geography at Humboldt University,
where the work shifted from subsurface to atmosphere - climate data, earth observation satellites,
computational modelling. Somewhere along the way, I realized the tools I needed didn't exist.
So I started building them.
Now I write Python instead of field reports. I build LLM-powered systems that crawl, extract,
learn, and adapt. The geoscience training never left - it just evolved into a different kind
of excavation.
04Technical Stack
Languages & Web
Python 3.x
TypeScript / Node.js
Express.js
HTML / CSS
R (RStudio)
AI & Automation
Agentic Systems (LLMs)
Open WebUI
Headless Web Scraping
Telegram Bots
Process Automation
Data & GeoScience
3D Geomodelling (Petrel)
Spatial Analysis (QGIS)
Climate Data Analytics
Real-time APIS (FIRMS, USGS)
Pandas / NumPy
Infrastructure
Server-Sent Events (SSE)
REST API Architecture
Hugging Face Spaces
Docker / Appwrite
Git / PowerShell
05Contact
Looking for a PhD position
in computational geoscience
or climate AI.
Also open to research collaborations, interesting side projects,
or anything where geoscience meets code. Based in Berlin.