Skills
Quantum Computing, optimization, machine learning, quantum error correction, HPC, Python, Qiskit
About
I develop and study quantum algorithms with a focus on making them practical
for near-term hardware. My current research centers on quantum optimization, quantum resources and quantum machine learning, bridging theory and experiment through close collaboration
with industry, including three years working with eleQtron GmbH to implement
noise mitigation and encoding strategies on trapped-ion processors. This work
has produced multiple publications and reinforced my conviction that useful quantum
computation requires algorithms tailored to specific platforms. While my primary expertise is in trapped ions, I maintain broad interest in the field, including familiarity with neutral atoms and
superconducting qubits, a strong interest in quantum error correction and a background in quantum many-body physics. I aim to contribute to both near-term applications and the longer-term goal of scalable, error-corrected quantum computing.
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