Papers

1

Total Citations

12

H-Index

1

About

Dominik Leib is a researcher at the forefront of quantum computing applications in industrial optimization, with a particular focus on bridging the gap between emerging quantum technologies and real-world scheduling challenges. His most notable work centers on benchmarking quantum-hybrid and quantum-inspired computing platforms against classical solvers for practical combinatorial optimization problems. Leib's landmark 2023 study presents one of the field's most thorough comparative analyses, pitting D-Wave's quantum-classical hybrid framework and Fujitsu's quantum-inspired digital annealer against Gurobi's industry-leading classical optimizer in tackling a transport robot scheduling problem drawn from genuine industrial settings. This work is particularly valuable because it moves beyond theoretical promise, grounding quantum computing assessments in realistic operational constraints that industries actually face. With 12 citations already accrued, the study has quickly gained traction among researchers navigating the noisy intermediate-scale quantum era. Leib's contributions are especially meaningful for students and practitioners trying to understand where quantum and quantum-inspired technologies genuinely stand today. By providing rigorous, reproducible benchmarks, he helps the community make informed decisions about when and whether to adopt these novel computational approaches over established classical methods.

Research Focus

Key Achievements

1
H-Index
1
Papers
12
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
An optimization case study for solving a transport robot scheduling problem on quantum-hybrid and quantum-inspired hardware
12 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Fraunhofer Institute for Industrial Mathematics

Top Papers

  1. 1

Key Collaborators

Contact & Links

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