Péter Hegedűs received his PhD degree in computer science from the University of Szeged in 2015. He currently works as a researcher both at the Software Engineering Department of University of Szeged and the MTA-SZTE Research Group of Artificial Intelligence.
His research interests include software maintainability models, deep learning applications, source code analysis, and vulnerability detection and prediction. He was a PC member in the CSMR, MSR, ICCSA and SQM conferences and currently holds a Bolyai János research scholarship. Besides teaching and research involvement, he also takes part in various software development projects as a project manager and lead developer.

Selected publications

  • Rudolf Ferenc, Tamás Viszkok, Tamás Aladics, Judit Jász, and Péter Hegedűs. Deep-water framework: The swiss army knife of humans working with machine learning models. SoftwareX, 12:100551, 2020.
  • Rudolf Ferenc, Péter Hegedűs, Péter Gyimesi, Gábor Antal, Dénes Bán, and Tibor Gyimóthy. Challenging Machine Learning Algorithms in Predicting Vulnerable JavaScript Functions. In Proceedings of the 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering, pages 8-14. IEEE Press, 2019.