Building autonomous systems that operate in the real world
I'm a Mechanical Engineering student who lives at the intersection of hardware and software — designing drone frames by day and writing ROS 2 nodes by night. My research at IIT Hyderabad focused on stereo vision pipelines for depth estimation and obstacle detection, deployed on Raspberry Pi and Hailo-8 AI accelerators.
I believe in India's vision of technological self-reliance by 2047, contributing through open research, funded UAV projects, and building the next generation of robotics engineers as President of YugTroniX.
Internships, leadership, and technical coordination
Worked on Stereo Vision-Based Obstacle Detection & Depth Estimation. Calibrated IMX219 and ZED cameras; generated disparity maps using OpenCV with CLAHE preprocessing and WLS filtering. Integrated YOLO v5/v7/v8 with DBSCAN spatial clustering for distance-aware detection. Deployed full pipeline on Raspberry Pi and Hailo-8 AI accelerator. Built ArUco marker-based multi-robot tracking system for outdoor terrain mapping.
Leading 30+ members in mechanical design and embedded systems. Directing technical operations, sourcing hardware for quadcopter builds, overseeing autonomous flight code development using PX4 and ROS 2.
Established club infrastructure, ran technical workshops on ArduPilot, QGroundControl, and Fusion 360. Led the quadcopter development team from first wiring to autonomous flight.
Official MyGov Campus Ambassador. Co-organised Bold Beginnings, fostering startup culture, hardware innovation, and student leadership development.
Built and maintain front-end platforms in HTML, CSS, and JavaScript. Managing digital presence for a national-level technical symposium and 150+ member student chapter.
CGPA: 8.53 / 10 through 4th Semester. Recipient of ₹20,000 KEATS Scholarship for academic excellence. Specialising in robotics, autonomous systems, and UAV design.
Percentage: 96.9%
GPA: 10 / 10 (100%)
Competitions, grants, fellowships, and scholarships
Tools, frameworks, and languages across the full robotics pipeline
Autonomous systems, perception pipelines, and real-world robotics
Peer-reviewed contributions to robotics and autonomous systems
Developed a stereo vision monitoring system using ArUco markers to track multiple mobile robots in GPS-denied outdoor environments. Research covers multi-robot SLAM using ROS 2 and Raspberry Pi 5 — addressing real-time localization, disparity-based depth accuracy, and inter-robot coordination for collaborative terrain mapping at scale.
Open to research collaborations, internships, and technical discussions