I am an M.Tech student in Computer Science and Engineering with hands-on experience building end-to-end AI applications, including real-time computer vision systems and interactive web platforms.
I work with YOLOv8, OpenCV, TensorFlow, Scikit-learn, and Python to develop machine learning and object-detection solutions. My work includes real-time vehicle detection, lane tracking, fog estimation, and image-processing pipelines.
I also build backend and frontend applications using FastAPI, Node.js, Express.js, React, and Next.js. I have experience integrating MongoDB, WebSockets, and JWT authentication to create responsive, secure dashboards and APIs.
As a Teaching Assistant in the Department of Computer Science and Engineering, I conduct and assess Operating Systems and Compiler Design labs for more than 150 students. I have designed structured evaluation workflows that improve grading consistency and turnaround time.
I am interested in AI/ML engineering, computer vision, deep learning, and full-stack AI product development. I continue to develop my knowledge of Mixture-of-Experts architectures, knowledge distillation, and fine-tuning pretrained models.
I conduct and assess Operating Systems and Compiler Design laboratory sessions for more than 150 students.
I designed a structured evaluation workflow for over 100 student projects, helping ensure consistent grading and faster feedback turnaround.
M.Tech, Computer Science and Engineering
CGPA: 8.45/10.
B.Tech, Computer Science and Engineering
CGPA: 8.45/10.
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