I am focused on Computer Vision, Deep Learning, and scalable MLOps systems. My work spans object detection, semantic segmentation, action recognition, multimodal AI, and generative models for image and video. I build end to end ML pipelines from data processing to model deployment using PyTorch, TensorFlow, FastAPI, Docker, and cloud native tools. I’m passionate about designing high performance AI systems, optimizing latency, and creating practical, production grade solutions that drive real world impact.
With hands on experience in AI engineering, I enjoy turning ideas into practical, reliable systems that create real value. I love exploring new approaches in computer vision and DL, pushing models beyond benchmarks, and building technology that works both in theory and in the real world. Driven by curiosity and continuous improvement, I focus on crafting solutions that are not only technically strong but meaningful, impactful, and scalable.
Python, JavaScript, HTML, CSS, React.js, FastAPI, MongoDB, PyTorch, TensorFlow, AWS
M.S. in Computer Science (GPA: 3.82/4.0), University of Bridgeport, CT.
Developed 4 computer vision and DL projects and built 3 full-stack web applications, deploying them successfully.
Here are the skills and capabilities I’ve built over time while developing full stack web applications and deploying them to production environments. My expertise extends beyond traditional development, my command of modern AI tools and frameworks is reflected in the real world projects I’ve delivered, creating systems that are both intelligent and highly user focused.
I focus on building deep learning and computer vision projects that are practical, reliable, and impactful in real world applications. It includes developing models for tasks like object detection, segmentation, and image understanding, while ensuring they are efficient, responsive, and production ready. I enjoy turning ideas into working AI systems that solve meaningful problems and integrate smoothly into modern software environments.
I work extensively with PyTorch, TensorFlow, OpenCV, Kaggle, and Google Colab, using these tools to develop and experiment with deep learning and computer vision models. They’ve enabled me to build systems that are efficient, well optimized, and effective in real world scenarios. My experience covers everything from data preparation and model training to creating reliable, production ready AI components that integrate smoothly into full stack applications.
I build modern, full stack web applications that are responsive, scalable, and optimized for real world use. Using the latest frameworks and best practices, I focus on delivering clean interfaces, seamless API integration, and strong performance across all devices. My experience also includes end to end deployment, ensuring that applications run smoothly in production environments with reliability and efficiency.
I have experience working with PostgreSQL, MySQL, and MongoDB, using them to design reliable, well structured data layers for full stack applications. I’ve deployed projects using modern cloud platforms such as AWS, Render, and Vercel, ensuring smooth performance, secure configurations, and dependable uptime. This combination of database and cloud knowledge helps me build applications that are both scalable and robust in real world environments.
Welcome to my web development portfolio! Here’s a look at the projects I’ve been building ranging from full stack web applications to AI/ML powered tools designed to solve practical real world challenges.
msbani19@gmail.com
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