Research Themes
My work centers on harnessing deep learning and computer vision to interpret visual data and build intelligent systems. I'm drawn to projects that turn raw pixels into actionable understanding.
Current Projects
I'm exploring real-time video processing, efficient recognition pipelines, and applications that bring AI into everyday tools.
Future Directions
Going forward I plan to investigate lightweight models for edge devices and responsible approaches for deploying computer vision in the wild.
Project Highlights
Real-Time Video Matting
Novel deep learning technique for high-quality background removal in videos.
Automatic Vehicle Counting
Computer vision system that accurately counts and tracks vehicles in traffic footage.
Face Recognition Toolkit
Modular pipeline for face detection and recognition using deep neural networks.
Milestones & Publications
2024
Face Recognition Toolkit v1.0
Released a modular pipeline for robust face detection and recognition.
2023
Automatic Vehicle Counting Deployed
Launched traffic-monitoring system used for urban planning studies.
2022
Real-Time Video Matting
Published method for live background removal in video streams.