Sebastian Feld
Associate Professor at Delft University of Technology
About
Sebastian Feld is an associate professor at Delft University of Technology, The Netherlands, where he works on full-stack quantum computing from architecture to applications. His research asks how quantum computers should be designed, programmed, and operated so that promising algorithms can become reliable computations on real hardware. Together with his group, he develops scalable quantum architectures, hardware-aware compilation methods, techniques for reliable quantum computation, and quantum algorithms for realistic optimization, planning, and engineering problems. Previously, he led the Quantum Applications and Research Laboratory (QAR-Lab) at LMU Munich, focusing on quantum-assisted artificial intelligence and optimization. He earned his doctorate from LMU Munich with research in time series analysis.
Experience
Associate Professor
Delft University of Technology
Oct 2026 – Present
Sebastian Feld is an associate professor at Delft University of Technology, The Netherlands, where he works on full-stack quantum computing from architecture to applications. His research asks how quantum computers should be designed, programmed, and operated so that promising algorithms can become reliable computations on real hardware. Together with his group, he develops scalable quantum architectures, hardware-aware compilation methods, techniques for reliable quantum computation, and quantum algorithms for realistic optimization, planning, and engineering problems. Previously, he led the Quantum Applications and Research Laboratory (QAR-Lab) at LMU Munich, focusing on quantum-assisted artificial intelligence and optimization. He earned his doctorate from LMU Munich with research in time series analysis.
Independent
Oct 2026 – Present
Sebastian Feld is an associate professor at Delft University of Technology, The Netherlands, where he works on full-stack quantum computing from architecture to applications. His research asks how quantum computers should be designed, programmed, and operated so that promising algorithms can become reliable computations on real hardware. Together with his group, he develops scalable quantum architectures, hardware-aware compilation methods, techniques for reliable quantum computation, and quantum algorithms for realistic optimization, planning, and engineering problems. Previously, he led the Quantum Applications and Research Laboratory (QAR-Lab) at LMU Munich, focusing on quantum-assisted artificial intelligence and optimization. He earned his doctorate from LMU Munich with research in time series analysis.
