Digital Crop Science
Building models, simulations, and ML systems for plant-soil problems.
M.Sc. Crop Science with a digital focus. I combine domain expertise in plant physiology with modern software engineering to solve agricultural challenges.
What I Do
Three interconnected areas of expertise that I bring to every project.
ML & Computer Vision
Deep learning pipelines for plant phenotyping, image segmentation, and classification systems.
Modeling & Simulation
Mathematical models and simulations for soil-plant systems, rhizosphere dynamics, and growth prediction.
Research Engineering
Reproducible pipelines, CI/CD for research, containerization, and deployment of scientific tools.
Featured Work
Selected projects showcasing my approach to solving complex problems.
Helios Intercropping Pipeline
GPU-accelerated synthetic data generation for faba bean and wheat intercropping research using 3D plant simulation.
GrowController: IoT Environmental Monitor
ESP32-based CO2, temperature, and humidity monitor with VPD calculation and Prometheus/Grafana integration.
Multispectral UAV Crop Classification Pipeline
Complete ML/DL pipeline for crop classification using multispectral UAV orthoimages with temporal analysis and spatial-aware train/test splits.
How I Work
Scientific Rigor
Every model is grounded in domain knowledge and validated against real data.
Reproducibility
Version-controlled code, containerized environments, and documented workflows.
Clean Engineering
Type-safe code, tested pipelines, and maintainable architectures.
Collaboration
Clear documentation, modular design, and open communication.
Let’s Work Together
I’m currently seeking opportunities in AgTech, biotech, or research institutions. Whether it’s a PhD position or an industry role, I’m ready to contribute.