Shivansh M.

I evaluate, prototype, and document quantum and post-quantum systems. My work focuses on PQC migration roadmaps, QKD network simulations, quantum algorithm benchmarks, and scientific ML or QML pipelines. My background is in physics and quantum communication. For my MS thesis, I simulated QKD networks to analyze routing, resource allocation, and QBER behavior under noise constraints. Since then, I have built hybrid ML pipelines for materials prediction, drafted PQC migration strategies, and evaluated quantum algorithms for power grid infrastructure. What I do: - PQC migration: Cryptographic inventory, risk assessments using NIST standards, and phased transition planning. - Network simulation: Modeling BB84, QBER, error correction, and resource allocation. - Algorithm benchmarking: Code development and performance testing using Python, Qiskit, and -PennyLane. - Scientific ML & QML: Debugging and optimization of hybrid workflows. - Technical writing: Clear documentation for engineering, policy, and executive teams. I focus on the intersection of applied physics and quantum engineering. I help teams separate near-term utility from quantum hype, translate academic research into clean code, and write technical reports that stand up to expert review.