Delhi, India
Dhruv Kumar Aspiring Computer Science Expert Education: Bachelor of Technology in Computer Science and Engineering SRM Institute of Science and Technology, Delhi NCR Campus Expected Graduation: 2027 Hi, I'm Dhruv Kumar, a passionate and dedicated Computer Science undergraduate at SRM Institute of Science and Technology, Delhi NCR. I'm on an exciting journey to build a strong career in technology, with a particular interest in software development, machine learning, and artificial intelligence. I love solving problems, thinking analytically, and constantly pushing myself to innovate and create through coding. Academic Journey I'm currently pursuing my B.Tech in Computer Science and Engineering, where I focus not just on theoretical knowledge but also on applying it practically through various projects. My work mainly revolves around AI and machine learning, areas that fascinate me and drive my creativity. I actively participate in coding competitions and hackathons, always looking for opportunities to challenge myself and learn new skills. Technical Skills -Languages:* Python, C, C++, -Technologies & Tools:* TensorFlow, Git -Frameworks & Databases: SQL, MongoDB Career Goals After completing my degree, I aim to work in a leading tech company where I can contribute to innovative projects, especially in AI and machine learning. I am passionate about using technology to solve real-world problems and create meaningful impact. My dream is to keep learning, growing, and building solutions that make a difference. Get in Touch - Email: [email protected]
Core member of the AI/ML team at GDG on Campus SRM, contributing to [specific activity — e.g., "technical sessions on machine learning fundamentals," "a hands-on workshop on X," "mentoring junior members on ML projects"]. [One line on scale/impact — e.g., "Helped organize sessions reaching 100+ students" or "Built and presented a project on X to the community."
Engineered real-time Computer Vision pipelines using Python, OpenCV, and CNN-based detection models for human detection in live drone aerial imagery, achieving sub-200ms inference latency under operational field constraints — end-to-end ML engineering from raw data to deployed model.
Completed a virtual internship with Edunet Foundation, where I designed and implemented a deep learning-based plant disease detection model. The project involved data preprocessing, convolutional neural network training, and performance evaluation to enable accurate early detection of plant diseases, contributing to sustainable agricultural practices. This experience strengthened my expertise in applied AI, computer vision, and model optimization for real-world impact.