Papers

4

Total Citations

107

H-Index

4

About

Vasilios N. Katsikis is a leading researcher at the intersection of neural computation, matrix theory, and robotics. His work primarily focuses on developing advanced numerical methods for solving complex, time-varying linear systems, with a particular emphasis on quaternion and complex-valued matrix equations. Katsikis has made seminal contributions to the field of zeroing neural networks (ZNN), pioneering higher-order ZNN models for calculating quaternion matrix inverses and pseudoinverses—critical tools for applications in robotic motion tracking and angle-of-arrival localization. His most cited work, a 2021 study on solving complex-valued time-varying linear matrix equations via QR decomposition, has garnered 77 citations and directly addresses fundamental challenges in engineering and science. More recently, he has expanded into neuromorphic computing, authoring a comprehensive 2025 survey on spiking neural networks (SNNs) that systematically reviews training methodologies, hardware implementations, and practical applications. With a portfolio of highly cited papers and a clear trajectory from theoretical matrix computations to cutting-edge neural architectures, Katsikis stands as a versatile and impactful figure whose work bridges pure mathematics with real-world robotic and AI systems.

Research Focus

Key Achievements

4
H-Index
4
Papers
107
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
Solving Complex-Valued Time-Varying Linear Matrix Equations via QR Decomposition With Applications to Robotic Motion Tracking and on Angle-of-Arrival Localization
77 citations · 2021
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: National and Kapodistrian University of Athens, Democritus University of Thrace

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago