About
AI Engineer with hands-on experience in Machine Learning and Deep Learning, specializing in Computer Vision, NLP, and sensor-based activity recognition. Skilled in building end-to-end AI pipelines using Python, PyTorch, TensorFlow, and OpenCV. Passionate about applying AI to real-world problems in sports analytics, healthcare, and automation.
Projects
Player Re-Identification (YOLOv8+ TorchReID)
Developed a pipeline to detect, track, and re-identify football players, integrating OCR for jersey number recognition.
View on GitHub →
Sensor Data Processing for Exercise Recognition
Built ML models to classify barbell exercises and count repetitions from MetaMotion sensor data.
Source →Open Source Contributions
Py-Easy-Env: The Visual Python Environment Manager
A modern graphical user interface (GUI) for managing Python project dependencies and environments — without the hassle of complex command-line workflows. Inspired by tools like Poetry and Pipenv, but designed with simplicity and visual ease in mind.
View on GitHub →