I'm a developer and researcher passionate about computer vision, deep learning and building intelligent systems. I enjoy working on practical AI problems, from real-time object tracking to image analysis and automation tools. I'm comfortable across the stack, but I especially thrive in Python, Linux, and open-source ecosystems.
I'm always open to discussions and collaborations. You can find my professesional profile on LinkedIn or explore my YouTube or X account to know more about me.
As a hands-on developer and researcher, I’ve built expertise across a focused set of programming languages and tools that help me tackle real-world AI and computer vision challenges. Here are the languages and environments I use to turn complex ideas into practical, efficient solutions.
In the evolving world of AI and system deployment, I specialize in using cloud platforms and tools to build, optimize, and manage efficient, scalable, and reliable pipelines. From experimentation to deployment, I ensure the systems are production-ready and resource-efficient. Here's a look at the cloud and deployment technologies I work with:
Frameworks play a key role in my development workflow, enabling me to build intelligent, efficient, and scalable systems with ease. I work with a range of frameworks that support rapid experimentation, smooth deployment, and robust functionality across machine learning, computer vision, and backend services.
Here are some of the eniroment technologies I regularly work with to build, experiment, and deploy intelligent systems.
I use following repositories for my setup:
- Arch linux post installation auto setup repository
- Neovim configuration repository
- Linux dotfiles repository