I am captivated by the field of Data Science and Artificial Intelligence, having a keen interest in understanding the inner-workings of Machine Learning Algorithms and Data Systems. Beyond that, how these theories are applied to the real-world using High-Performance computing, and sophisticated and distributed systems to the Peta-Bytes worth of data that exists on the internet. Yielding the skill-set under my possession, I seek to not only understand theoretical concepts like Machine-Learning, but also implement and enable them practically on real-world Big Data. I believe data is central to the utility of any system and high-performance computing and distributed systems are the tools that enable it to be used practically.

I rigorously pre-process and wrangle with data through techniques like feature engineering to squeeze out every last bit of information it may contain, then I analyze it to uncover its story and the information it is communicating, and finally I use the insights gained to forecast what it may predict. I use high-performance computing to ensure that I am utilizing the full potential of the hardware that is made available to me, and design my infrastructure in a way that can scale to utilize the potential of any future hardware upgrades.

I am collaborative, and welcome any open-source contributions, joint-project ventures or code-review assistance. My contribution to any project can bring the unique perspective of the project as a data systems solution. I look forward to contributing my knowledge to any project and possibly in exchange also learn a different perspective from my contributor.

• MLOps workflows
• RAG pipelines with LLMs
• ETL pipelines
• CLI tooling
• Blockchain
• High-Performance Simulations