I am an Electronics and Communication Engineering graduate from Siddaganga Institute
of Technology, Tumakuru, with a background in digital systems, signal processing,
embedded systems, and circuit analysis. During my final year, I led a research project
on early Alzheimer's disease detection from MRI scans using deep learning, which was
published at the 2024 IEEE International Conference on Smart Systems for Applications
in Electrical Sciences (ICSSES).
After graduating, I spent two years at Tata Consultancy Services as a Systems Engineer,
working as a support analyst for SAP Digital Manufacturing systems for Pandora A/S —
a global jewellery manufacturing company. The role involved large-scale enterprise system
integration, performance optimisation, and cross-functional technical support — an
experience that gave me a strong understanding of how complex systems behave under
real-world operational constraints.
Alongside my industry work, I completed a certification in Quantum Computing and Artificial
Intelligence at the Indian Institute of Science (IISc), Bengaluru, where I studied quantum
algorithms, quantum machine learning, and quantum cryptography. As part of this programme,
I built QryptChat — a secure chat application implementing the BB92 quantum key
distribution protocol to demonstrate secure communication between two parties.
My current research interest is in hardware-aware quantum circuit design for NISQ
devices — specifically, developing automated frameworks that generate circuit
architectures natively compatible with real quantum hardware, using multi-objective
optimisation to balance accuracy, circuit depth, and noise resilience.
More broadly, I am drawn to the intersection of machine learning, quantum computing, and
systems-level thinking — building algorithms that perform not just in theory, but
on the hardware that actually exists today.
