Brief Biography

I am a distinguished computer science professional with a rich educational background from NIT Goa, complemented by a robust GPA of 9.12

My academic journey is marked by excellence, as demonstrated by my 92% in PCM in Class 12 and a stellar 96% in the ICSE class 10 board exams.

My professional experience includes impactful internships at Cyanodoc and C-DOT where I honed skills in Angular2, Android, Scapy, and Git, and further developed a mobile app incorporating medical diagnoses using Flutter on Android Studio. I have worked on projects involving Computer Vision, Deep Learning and Machine Learning at institutions like BITS Goa and National Institute of Oceanography. I have also bagged a national scholarship in tabla.

Ongoing Work: Development of Single Flux Quantum (SFQ) Architecture.

Impact: Current energy and environmental cost trend of CMOS based designs are unsustainable. Wire resistance and capacitance on the CMOS chip cause most of the delay. They also consume most of the energy and hence lead to power and heat struggles. As CMOS technology scaling slows, the search for post-CMOS technologies has intensified. There is an increasing demand for energy-efficient computing from applications such as high-performance simulations, machine learning algorithms, that require beyond petaflops of computing. Superconducting computing based on the Josephson Effect has the potential to meet these demands. These processors aim to provide fast and energy efficient computation in order to meet the growing demand.

Currently, rapid single flux quantum (RSFQ) logic is the leading superconducting digital computing logic family that is being researched as an alternative to CMOS. Arithmetic circuits play an important role in any machine learning, scientific, and DSP applications