B. Tech in Computer Science Engineering
Punjab Technical University, Main Campus, Jalandhar
3rd Year
- 🥇 1st Place in internal SIH Hackathon
- 🏅 Finalist, Code for Good Hackathon, IIT Mandi (Top 10 out of 550)
- 🏅 Finalist, Hackfest by IIT (ISM) Dhanbad (Top 70 out of 1200)
- 👨🏫 Mentored 50+ students in mobile app development & ML for a hackathon (Final at Microsoft Office Gurgaon)
- 📱 Developing a mobile app for my college (Undergoing testing)
- 🏅 Top 40 teams in IIIT Naya Raipur Hackathon (1,764 teams, Finals: 15th Sept 2024)
- 🏅 Finalist, Hack'Ndore (Top 100 out of 1100)
- 🔹 Advanced to the second round in Haryana Police Narcotics Control Bureau Hackathon and IGDTUW Hackathon
- 🔹 Advanced to the second round in Bank of Baroda Hackathon
- 🥈 Ranked Top 400 in HackWithIndia (Out of 1500 teams)
Cross-platform fitness app using AI/ML for workout plans, diet, mental health tracking, and more.
Python-based vehicle classification and counting using ML, Computer Vision, and Deep Learning.
Summarizes and links articles using advanced NLP techniques.
AI chatbot for legal queries in English and scheduled Indian languages.
This research introduces a novel method utilizing micro-Doppler radar signatures to detect drones based on the unique motion characteristics of their rotors. By analyzing the micro-Doppler patterns generated by drone rotor movement, the system enhances the detection and classification of airborne objects. Advanced algorithms are employed to distinguish these patterns, providing a reliable system for drone detection. The method is especially applicable to areas such as military defense, airport security, no-fly zone enforcement, and protection against drone-based threats. The work also includes a comparative analysis of existing drone detection methods, addressing the increasing need for scalable and dependable solutions in airspace security and safety across critical sectors.
Submitting for Lance Stafford Larson Student Award 2024
Full Stack Developer Intern (Remote) | May 2024 – July 2024
- Developed front-end interfaces using HTML, CSS, JavaScript, React.js, and Flutter, enhancing user experience for the Saarthi AI platform.
- Implemented back-end functionalities with Node.js and Express.js, and managed databases with MongoDB for efficient, scalable data handling.
- Collaborated with cross-functional teams and utilized AWS Cloud services to contribute to a platform focused on promoting Indian culture and supporting local businesses.
Member | August 2023 – August 2024
- Engaged in Android app development, contributing to various projects and initiatives.
- Advanced techniques in Machine Learning for Computer Vision.
- Cross-platform mobile development with Flutter, Firebase, and MongoDB.
- Machine Learning and Computer Vision.
- 📧 Email: [email protected]
- 🔗 LinkedIn: linkedin.com/in/devesh-kaushal-605985248/
- 🐦 Twitter: @DeveshKaushal10
- Enhancing Airborne Drone Detection Through Micro-Doppler Radar Signatures
Submitting for Lance Stafford Larson Student Award 2024