Aug 2025 to Dec 2025
Image-Based Forest Analysis & Optimal Path Computation
A computer-vision research project accepted at an IEEE International Conference. It covers an end-to-end ML data pipeline (annotation, augmentation, and preprocessing) culminating in a trained and benchmarked YOLOv8 model for forested-area analysis and optimal path computation.
PythonOpenCVYOLOv8Machine Learning
IEEE
Publication
YOLOv8
Model
ML Data Pipeline
I engineered an end-to-end ML data pipeline covering annotation, augmentation, and preprocessing, then trained and benchmarked a YOLOv8 model with balanced precision-recall metrics.
Documentation & Delivery
I authored architecture documentation, preprocessing pipeline specs, and a structured test plan, and delivered stakeholder-ready progress reports at each milestone. This work was accepted at an IEEE International Conference.