13 years of intelligence experience — now building systems at the intersection of computer vision and geospatial analytics designed to transform raw sensor data into actionable location intelligence.
⚡ Core Competencies: Machine Learning, Computer Vision, Geospatial Analytics, Predictive Modeling.
🎯 Goal: Improve the speed at which analysts can inform decisions and drive action.
🛠️ Technical Stack:
- 👁️ CV & DL: YOLOv8 | OpenCV | Multi-Object Tracking (Supervision) | Homography | Image Filters | Real-Time Image Processing
- 🧠 ML & Stats: Regression | Classification | Clustering | Model Evaluation | Hypothesis Testing | Markov Chains | Kalman Filtering
- 🌐 Geospatial: Shapely | GeoPy | Folium | Trajectory Analysis | Pattern-of-Life Analysis | Stay-Point Detection | GeoPandas
- ⚙️ Data Processing: Python (Pandas, NumPy) | SQL | ETL Workflows | Java | Feature Engineering
- 💻 Dev & Deliver: Git | GitHub | VS Code | Conda | Bash | Streamlit | Dashboard Development | Technical Reporting
🗺️ Traffic Conflict Detection: Computer vision system that detects, catalogues, and geolocates vehicle conflict events from traffic camera footage by transforming pixel-space coordinates into real-world geographic coordinates.
Geolocation within 1.47 meters (RMSE)
📡 Pattern-of-Life Analysis Toolkit: Python package + Demo App for evaluating, processing, analyzing, and modeling individual-level mobility derived from location-based services.
Processed over 350,000 GPS traces
🚗 Lane Detection Classic: Lane-line detection pipeline that combines classical computer vision techniques with traditional machine learning.
0.94-0.99 R2 scores
I'm chilling with Dude (my son), Pumpkin (daughter 1), Lady Bug (daughter 2), and Angel (my wife). If the weather's nice, you might find me flat-water kayaking at a lake near my home. If the weather's a little mean I'll probably be inside reading a book (I'm exploring casual non-fiction...we'll see how it goes). On the weekends, I'm in the kitchen cooking or baking (I'll fight you with my pancake recipe!). Regardless of the weather or the day of the week, I love learning and am always looking for ways to be better.
I'm always open to a discussion on anything related to coding or the data science profession at large. Drop me a line and I'll probably get back to you in the evening while enjoying a glass of wine (got to get the kids down first).