I’m a Computer Vision & Deep Learning Engineer focused on real-time perception, 3D calibration/triangulation, and GPU-accelerated optimization.
Currently am working at Quidich Innovation Labs, I lead vision initiatives powering broadcast-grade ball tracking and calibration across 4K, High FPS, multi-camera setups—using TensorRT, CUDA, and NVIDIA DALI to hit sub-ms sync and dramatically reduce trajectory error. Also, image stabilisation methods to preseve the calibration in outdoor sports environment when the cameras are zoomed in.
I also build surveillance and smart-city solutions (action recognition, abandoned-object detection, traffic analytics, ID/OCR), synthetic data pipelines (Unity/Unreal/Blender/Omniverse), and deploy on Jetson and cloud with rigorous performance tuning.
Sardar Vallabhbhai National Institute of Technology, Surat — M.tech
Vishwakarma Institute of Information Technology, Pune — BE, Pune University. 72% First Class with distinction
Spearheaded development of an advanced cricket ball tracking system integrating precise camera calibration, real-time ball detection, and small object detection at 400 FPS in 4K resolution. Utilized GPU Direct across 10 cameras to reduce ball trajectory prediction error by 90% compared to state-of-the-art methods.
Engineered a novel on-ground camera calibration method using a total station combined with bundle adjustment, achieving millimeter-level triangulation accuracy from distances up to 200 m.
Developed a real-time scene classifier for QuickFlip—the world’s first vertical feed for sports—to enhance content relevance and viewer engagement.
Developed end-to-end Jetson-based surveillance & inventory detection for Ivory Soaps to detect inventory theft and monitor security using object detection and GenAI for pharmaceutical research.
Enhanced synthetic data model training for AuraML, improving YOLOv5 fine-tuning by 25% mAP, and implemented SLAM-based navigation with photogrammetry for 3D environments.
Created a novel algorithm to detect abandoned objects on highways using CUDA, MOG2, and object detection with 94% accuracy.
Developed highly optimized models and algorithms in C++ for Nvidia Jetson boards, leveraging DLAs to run multiple models concurrently on shared resources.
Developed 3D computer vision-based human body tracking and advanced human motion analysis for exercise routines, including detection of equipment and usage patterns during workouts.
Developed an ID card recognition system to extract information/photos from PAN, AADHAAR, and international passports (including MRZ codes).
Managed traffic density analysis by controlling traffic signal countdowns using TensorRT and YOLOv4 on Jetson devices; provided detailed traffic stats for toll plaza planning using DeepSort.
Implemented pothole and garbage detection on car cameras using EfficientDet and TensorRT, reporting GPS locations to government entities (BBMP and KRDCL).
Utilized object detection, pose estimation, and ConvLSTM for smart city surveillance to identify potential security threats and monitor human activity.
Developed exercise video analysis solutions including E-Gym tracking for Koofit and Mediapipe BlazePose–based exercise tracking for UPUGO.
Performed trajectory analysis of sports balls using object detection and tracking algorithms, visualizing data on a 2D pitch map with heatmaps.
Developed athlete form correction methods for cricket batting and bowling using advanced pose estimation techniques.
Automated B2C marketing campaigns and analytics across major social media platforms.
Developed object detection–based hashtag recommendation systems and performed sentiment analysis on large-scale social media data.
Accomplished Indian strength sport athlete with about a dozen awards on national level, state level(Gujarat and Maharashtra)and University Games.
Shortlisted to represent India for International powerlifting games July 2020
Qualified GATE 2019 with 2326 All India Rank