Predicting Tennis Match Outcomes with Network Analysis and Machine Learning. - Firas Bayram; Davide Garbarino; Annalisa Barla (SOFSEM, 2021)

A Drift Handling Approach for Self-Adaptive ML Software in Scalable Industrial Processes. - Firas Bayram; Bestoun S. Ahmed; Erik Hallin; Anton Engman (ASE, 2022)

A systematic mapping study of source code representation for deep learning in software engineering. - Hazem Peter Samoaa; Firas Bayram; Pasquale Salza; Philipp Leitner 001 (IET Softw., 2022)

From concept drift to model degradation: An overview on performance-aware drift detectors. - Firas Bayram; Bestoun S. Ahmed; Andreas Kassler (Knowl. Based Syst., 2022)

DQSOps: Data Quality Scoring Operations Framework for Data-Driven Applications. - Firas Bayram; Bestoun S. Ahmed; Erik Hallin; Anton Engman (EASE, 2023)

DA-LSTM: A dynamic drift-adaptive learning framework for interval load forecasting with LSTM networks. - Firas Bayram; Phil Aupke; Bestoun S. Ahmed; Andreas Kassler; Andreas D. Theocharis; Jonas Forsman (Eng. Appl. Artif. Intell., 2023)

AIDA - A holistic AI-driven networking and processing framework for industrial IoT applications. - Hamza Chahed; Muhammad Usman 012; Ayan Chatterjee; Firas Bayram; Rajat Chaudhary; Anna Brunström; Javid Taheri; Bestoun S. Ahmed; Andreas Kassler (Internet Things, 2023)

A domain-region based evaluation of ML performance robustness to covariate shift. - Firas Bayram; Bestoun S. Ahmed (Neural Comput. Appl., 2023)

Adaptive data quality scoring operations framework using drift-aware mechanism for industrial applications. - Firas Bayram; Bestoun S. Ahmed; Erik Hallin (J. Syst. Softw., 2024)

Quality Assurance for LLM-RAG Systems: Empirical Insights from Tourism Application Testing. - Bestoun S. Ahmed; Ludwig Otto Baader; Firas Bayram; Siri Jagstedt; Peter Magnusson (ICSTW, 2025)

Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach. - Firas Bayram; Bestoun S. Ahmed (ACM Comput. Surv., 2025)