George G. Cabral

George G. Cabral is an Assistant Professor (Lecturer) in the Department of Computing at the Federal Rural University of Pernambuco (UFRPE) in Recife, Brazil. His academic career spans research and teaching in machine learning, with a particular focus on applications to software engineering and other real-world domains.

• Ph.D. in Computer Science, Federal University of Pernambuco (2014)
• M.Sc. in Computer Science, Federal University of Pernambuco (2008)
• B.Sc. in Computer Engineering, University of Pernambuco (2005)
• PostDoc, University of Birmingham (2019)

Dr. Cabral's research primarily focuses on machine learning algorithms applied to real-world problems, with special emphasis on online learning and concept drift in data streams. His work explores class imbalanced learning techniques, ensembles of learning machines, and novelty detection methods. A significant portion of his research applies these techniques to software defect prediction, where he investigates just-in-time approaches that can identify potential bugs as software is being developed. He also applies similar methodologies to intrusion detection systems and public accounting domains, demonstrating the versatility of his research interests across different application areas.

Analysis of Dr. Cabral's publication history reveals a consistent trajectory from foundational work on one-class classification techniques toward increasingly applied research in software engineering contexts. His most recent publications (2022-2023) demonstrate expansion into public sector applications, particularly in data auditing for Brazilian municipal governments, while maintaining his core focus on concept drift challenges in software defect prediction. The publications consistently address methodological challenges like verification latency and class imbalance evolution in streaming data environments.

Dr. Cabral actively contributes to the academic community as a committee member for the Artifact Evaluation track at major software engineering conferences including ASE (Automated Software Engineering) since 2021 and ICSE (International Conference on Software Engineering). He serves as a reviewer for journals such as Neurocomputing and Applied Soft Computing, and has taught undergraduate courses including Artificial Intelligence, Neural Networks, Computing Theory, and Programming at UFRPE.