Skills
TECHNICAL SKILLS
• Programming: Python, NumPy/SciPy, Jupyter, Git, Linux, HPC workflows
• Quantum software: Qiskit (Primitives, transpiler, runtime), custom ans¨atze, noise-aware
sampling pipelines
• Simulation and benchmarking: Aer (statevector, MPS), shot-based evaluation, heavy-
output and feasibility metrics
• Optimization methods: QUBO/Ising mapping, HUBO/PCE Mapping, routing and as-
signment models, hybrid grid search, classical baselines (MILP/MIQP)
About
I develop feasibility- and error-aware quantum optimization kernels that scale from noisy present-day devices to future fault-tolerant hardware, with a focus on constrained industrial problems like routing, assignment, and resource allocation. I am a theoretical physicist and doctoral research fellow at Volkswagen Group Innovation and RWTH Aachen University (Germany). I work at the intersection of constrained quantum optimization, variational quantum algorithms, and near-term quantum hardware benchmarking. My research focuses on structural mechanisms, including mixer geometry, spectral gaps, and symmetry, that determine when quantum optimization can scale beyond classical guarantees on NISQ and early fault-tolerant devices. My latest works include penalty-driven shallow-depth guarantees and Fej\'er-filtered finite-shot guarantees for constrained optimization, as well as encoded unitary design architectures for CE--QAOA.
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