Kővári Bence

Bence Kővári, Associate Professor at the Department of Automation and Applied Informatics, Budapest University of Technology and Economics, specializes in online signature verification, deep learning, and scheduling algorithms. His work bridges theoretical and applied computer science with engineering applications.

• University: Budapest University of Technology and Economics
• Department: Department of Automation and Applied Informatics
• Email: kovari@aut.bme.hu

Research Interests

His research focuses on biometric authentication through signature verification, integrating dynamic time warping and neural networks for efficient pattern recognition. He also explores fair scheduling in resource-constrained systems and applies deep learning to structural monitoring, notably in bridge weigh-in-motion systems.

Scientific Contributions

Kővári’s publications highlight advancements in signature verification (e.g., SVC-onGoing), feature selection, and bridge load estimation. His work spans interdisciplinary domains, including machine learning, signal processing, and optimization.

Scientific Awards

• SVC-onGoing: Signature verification competition (2022)
• ICDAR 2021 competition on on-line signature verification (2021)

Advising and Collaborations

While specific student names are not listed, Kővári actively contributes to academic research through publications, algorithm design, and participation in international competitions.