I am an engineer and applied research scientist with 20+ years of experience and expertise in diverse domains - embedded operating systems, language runtimes, security, cryptography & high-performance computing on edge devices.

I am very well versed in C, C++, Java, C#, Typescript & Python. I have been fortunate to design & develop real-world products with millions of users worldwide. However, these days Python has become my main language because of machine learning.

In the last few years, I have mastered deep learning with a special focus on computer vision, probabilistic programming, and generative networks. I have been fortunate to work on real-world problems in this space as well and the pace of research and discoveries in this area fascinates me.

After working on products in computer vision I was troubled by two main challenges - lack of explainability of modern deep models and how to include domain information in models. The latter helped me in discovering the Bayesian Probabilistic models and ever since I am on the journey to master the intricacies of this field.

My passion and strength lie in breaking complex subjects into simple to understand parts. I have always believed that sharing knowledge is a gift that one gives to himself/herself and I hope that with modern platforms for sharing the knowledge I can now reach out to more people.

This all being said, even after many years in the industry and experience with multiple domains, I consider myself a perpetual student of science and technology and still am excited by both theoretical underpinnings as well as real-world implementation details.