Dhruv Patel

• Orchestrated eight GDSC, GDG and other hackathon events across India, significantly enhancing developer engagement by attracting 10,000+ participants with strategic content and interactions
• Forged key partnerships with major tech leaders like Google, Amazon, Microsoft, along with various startups and communities in Web3 and AI, to fortify the ecosystem and enhance collaborative opportunities
• Led the conception and execution of a month-long hackathon, managing over 1,100 participants and 80+ projects with a total prize pool exceeding $50,000
• Organized and directed a 7-day Hacker House in Menlo Park, CA, providing a collaborative space for development and networking, enhancing the hackathon experience
• Served as the primary liaison for all partner and stakeholder communications, efficiently addressing inquiries and integrating feedback to refine community engagement strategies.
• Participated in regular code reviews, ensuring high-quality standards were consistently met across all development efforts.

• Developed a cost-effective, full-stack web application, Examify
• The application includes an interview questionnaire withindependent rounds at distinct levels
• Examify Achieved a 20% increase in qualified candidates and a 10% reduction in time-to-hire
• Leveraged knowledge in HTML, CSS, JavaScript, Laravel, React.js, MySQL, and Scientific Writing

• Engineered an advanced real-time Violence Detection System employing cutting-edge CNN and LSTM models
• Rigorouslytrained on a diverse dataset of ice hockey and football videos, the system demonstrated a remarkable accuracy of 92.3%
• Orchestrated the development of a Cross-Platform ML model for estimating body poses, fingertip locations, and real-time image classification model which seamlessly controlled virtual objects while achieving an impressive 91% accuracy in object recognition and mood detection
• Leveraged knowledge in Swift, SwiftUI, MLKit, CoreML, Scrum, UIKit, Realm
• MCTE – Centre of Excellence - AI, INDIAN

• Spearheaded built a Real-Time Image Segmentation technique based on Deep Learning that could run at 120 frames per second
• (60x faster than the previous algorithm)
• Led a team of 3 interns to design new AI-enabled surveillance that increased existing system accuracy by over 20% by replacing traditional surveillance techniques with automated AI-based Monitoring and Inference
• Leveraged knowledge in Deep Learning, Python, PyTorch, TensorFlow, Django, Scientific Writing, and some web frameworks
• Applied effective feature selection methods, reducing model complexity while maintaining high levels of predictive accuracy.
• Presented research at prestigious conferences, promoting knowledge sharing and collaboration within the scientific community.

• As a GDG Organizer of the New Brunswick chapter, I hosted 15+ events with 200+ attendees on fastest-growing technologies which created a technical community around the city
• Invited to attend Google I/O 2024 and met the CEO of Google.

• Evaluated over 100+ projects in 15+ Hackathons and gave an individual ranking, reviewed every docs
• And code.

• Spearheaded this technical community on campus which organized 10+ events and coached 200+ students.

• Executive & Financial committee member and I volunteered for various IEEE Technical events and Facilitated students.

3.9/4 GPA

GPA: 3.7/4