Headline

Final year student at VIT, Vellore | B.Tech Computer Science and Engineering | Autonomous System Engineer @ Team OJAS Racing | Real-Time Perception & Path-planning

About

As an Autonomous Systems Engineer at Team Ojas Racing, I've spent 2+ years developing the software stack for a Formula Student autonomous race car from real-time perception pipelines using YOLO and computer vision, to path planning algorithms built on ROS and Python. I don't just write code; I make systems that operate under real-world constraints at speed. What I work with: Path Planning & Decision Making (ROS 2, MATLAB) , Real-Time Perception (YOLO, OpenCV, Computer Vision) , Languages: Python, C++ , Tools : Robot Operating System (ROS/ROS 2), MATLAB, Machine Learning frameworks Beyond racing, I completed an internship at Virtusa in the Salesforce/CRM domain , giving me exposure to enterprise software environments and business process automation alongside my core robotics work. I'm a final year B.Tech Computer Science student at VIT Vellore, actively looking for full-time roles in autonomous systems / robotics engineering , computer Vision and perception engineering , AIML Engineering If you're building something that operates in the real world robots, vehicles, drones, or edge AI systems , I'd love to connect

Location

Vellore

AI stack

claude code

claude

gemini

langchain

ollama

openai

Work experience

Path Planning Engineer at Team Ojas Racing, Dec 2025 - Present · 10 mos, Vellore, As a member of the Path Planning team at Team Ojas Racing, I contribute to the development of autonomous navigation algorithms for a Formula Student Driverless vehicle. My work involves designing and implementing path planning solutions that enable the vehicle to navigate safely and efficiently in dynamic racing environments.

Software Intern at Hindustan Aeronautics Limited, May 2026 - Jun 2026 · 2 mos, Bengaluru, Developed an Offline Aircraft Part Recognition System at HAL's Helicopter Division using YOLOv8, Flask, and OpenCV. Built three detection modes (Upload, Partial-Manual, and Live Tray Identification) to identify 20 aerospace components from webcam feeds and images, with Excel-based recognition logging, multi-layer false positive filtering, and a synthetic composite dataset pipeline using rembg for model training. The system operates fully offline within HAL's air-gapped network environment.

Enterprise Software Intern at Virtusa, May 2025 - Jul 2025 · 3 mos, Bengaluru, Karnataka, India, Completed a 2-month internship at Virtusa in the Salesforce domain, focusing on CRM development and business process automation. Gained hands-on experience with workflows, process builders, and Salesforce customization.

Member of Autonomous domain at Team Ojas Racing, Apr 2024 - Nov 2025 · 1 yr 8 mos, Vellore, Tamil Nadu, India

Education

Bachelor of Technology, Computer science and engineering, Vellore Institute of Technology

pre-university education, Physics, Chemistry, Mathematics and Computer Science, Narayana pu college

Public links

github: https://github.com/Veekshith2005