Welcome to my GitHub! I’m a data engineering and machine learning enthusiast passionate about applying technology to real-world problems. My main focus is using data, robotics, and machine learning to tackle global challenges in food system sustainability and climate change. I’m especially interested in building systems that bridge research and deployment for long-term, meaningful impact. I’m not afraid to get my hands dirty—whether that’s field-testing robotic systems in agriculture, supporting hardware deployments in remote locations, or working hands-on in agroforestry initiatives in West Africa. I believe the best solutions often start in the field.
- 🛰️ Machine Learning & Computer Vision for Real-World Systems
- 🛠️ Data Engineering & SQL Pipelines for City-Scale Datasets
- 🤖 Robotic Manipulation & Deep Reinforcement Learning
- 📊 Data Analysis & Visualization in Python
- 🌱 Focus: Global Food System Sustainability & Climate Solutions
Built an end-to-end image classification pipeline to identify strawberry runners using CNNs and Python-based visualizations. Supports more efficient agricultural management.
Developed a data engineering and SQL-based audit of the City of Chicago’s food inspection and business license datasets to uncover regulatory gaps and propose system improvements to support public health and safety.
Explored deep reinforcement learning for robotic manipulation in agro-food clutter clearance. Adapted and extended the Visual Pushing for Grasping framework with custom reward structures and agro-food-specific training regimens.
Machine Learning:
PyTorch, TensorFlow, OpenCV, Scikit-learn
Data Engineering:
Airflow, Hadoop, SQL, NoSQL, S3, MongoDB, DynamoDB, Neo4j, RDS, DBeaver, OpenRefine
Programming Languages:
Python, MATLAB
Robotics & Software:
ROS, Simulink, CoppeliaSim, Git, Linux
Visualization & Analytics:
Grafana, Tableau, Excel, ArcGIS, Matplotlib, Seaborn
Development Tools:
Jupyter, Google Scripts, LabVIEW
August 2022 – November 2024 | United Kingdom
- Provided hardware/software support for 100+ deployed agricultural robots.
- Built ML testing pipelines, edge-case detection tools, and data annotation workflows for edge-deployed vision models.
- Reduced issue resolution time by 50% and improved robotic harvesting speed through parameter optimization.
- Led the launch of a robotic precision husbandry service for strawberries.
November 2021 – March 2022 | Netherlands
- Built object-oriented, physics-based vacuum system simulations using MATLAB/Simulink.
- Verified model accuracy with real-world data visualized in Grafana dashboards.
- Simulated dairy farm vacuum systems to identify potential mechanical stress points.
I am passionate about using data and machine learning to:
- Improve food system sustainability
- Build climate-conscious technologies
- Develop resilient solutions for real-world systems