Computer Science Student | AI/ML Engineer
Passionate about Deep Learning, Machine Learning, and building intelligent architectures for the future.

• 🎓 Senior Computer Science Student (7th Semester), deeply focused on Artificial Intelligence and its applications.
• 🧠 My core focus and passion lie in AI, Machine Learning, and Deep Learning. I have a strong foundation in these fields and they remain my primary career trajectory for the future.
• 💻 Experienced in bridging complex AI models into production-ready full-stack systems using PyTorch, Python, and FastAPI.
• 💼 Actively seeking Internships in AI, Machine Learning, and Deep Learning to apply my engineering skills to real-world intelligent systems.

• Primary Focus (AI/ML): PyTorch, Deep Learning (CNNs, ResNet), Neural Networks, Computer Vision, AI Integrations
• Backend & Data: Python, FastAPI, PostgreSQL
• Full Stack & Deployment: React, TypeScript, Docker, GitHub Actions CI/CD

Developed an asynchronous, density-based traffic management system using YOLOv8 and SORT tracking. Features a deterministic safety-validated signal engine and real-time telemetry streaming via MQTT and InfluxDB. Optimized for real-time inference and edge deployment.

Engineered a specialized Computer Vision & Object Recognition Pipeline leveraging a ResNet-18 (PyTorch) architecture. Served the model for inference via FastAPI with a Streamlit visualization frontend. The entire pipeline is fully containerized with Docker and features automated Bandit security audits via CI/CD.