Adaptive AI-based auto-scaling for Kubernetes. - László Toka; Gergely Dobreff; Balázs Fodor; Balázs Sonkoly (CCGRID, 2020)

Low-Cost Optical Tracking of Soccer Players. - Gabor Csanalosi; Gergely Dobreff; Alija Pasic; Marton Molnar; László Toka (MLSA@PKDD/ECML, 2020)

Physical Performance Optimization in Football. - Gergely Dobreff; Péter Revisnyei; Gábor Schuth; György Szigeti; László Toka; Alija Pasic (MLSA@PKDD/ECML, 2020)

Predicting cloud-native application failures based on monitoring data of cloud infrastructure. - László Toka; Gergely Dobreff; Dávid Haja; Mark Szalay (IM, 2021)

Machine Learning-Based Scaling Management for Kubernetes Edge Clusters. - László Toka; Gergely Dobreff; Balázs Fodor; Balázs Sonkoly (IEEE Trans. Netw. Serv. Manag., 2021)

Optimizing and dimensioning a data intensive cloud application for soccer player tracking. - Gergely Dobreff; Marton Molnar; László Toka (Int. J. Comput. Sci. Sport, 2022)

Predicting QoE for Delay-critical services in Mobile Networks: A video conferencing case study. - Gergely Dobreff; Márk Szalay; Marton Molnar; László Varga 004; Bence Ladóczki; Attila Báder; Alija Pasic (IWSSIP, 2023)

Data Collection Framework for End-to-End Radio and Transport Network Quality Monitoring. - Gergely Dobreff; Márk Szalay; Bence Ladóczki; Marton Molnar; László Varga 004; Attila Báder; Alija Pasic (QoMEX, 2023)

Empowering ISPs with Cloud Gaming User Experience Modeling: A NVIDIA GeForce NOW Use-Case. - Gergely Dobreff; Dániel Frey; Attila Báder; Alija Pasic (ICIN, 2024)

A QoE and Availability-Aware Framework for Network Slice Placement and Resource Allocation. - Gergely Dobreff; Attila Báder; Alija Pasic (IEEE Access, 2025)