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From real-time crowd density estimation at Infosys Springboard to leading 800+ participant hackathons at ECHO Tech — my experience spans applied ML, backend systems, and technical leadership.
Project: DeepVision Crowd Monitor — Building a real-time crowd density estimation system using CSRNet and MCNN architectures in PyTorch, trained on the ShanghaiTech dataset. Developed an OpenCV preprocessing pipeline for frame extraction and normalization. Generates heatmap overlays for crowd density visualization. Implementing a real-time inference system with Flask and Streamlit dashboards for monitoring. Integrated alert mechanisms via SMTP and Twilio for threshold-based notifications. Containerized with Docker for deployment. Tracking metrics including MAE, FPS, and inference latency (ongoing).
Co-founded ECHO Tech and led the execution of hackathons with 800+ participants, handling sponsorship acquisition, logistics coordination, and event operations end-to-end. Actively mentoring students and team members in backend development, machine learning, and deployment practices.