Damiano Torre, Ph.D.
About
Degrees
Dr. Damiano Torre is an Assistant Professor at the University of Washington Tacoma in the School of Engineering & Technology, where he began his tenure in September 2024. Driven by a passion for advancing the field of software engineering, Dr. Torre's research interests focus on artificial intelligence, model-driven engineering, cybersecurity, and empirical software engineering. Before joining the University of Washington Tacoma, Dr. Torre made notable contributions to academia and research. From August 2023 to August 2024, he served as an Assistant Professor of Software Engineering at St. Mary's University in San Antonio, Texas. During his time at St. Mary’s, Dr. Torre, as Principal Investigator, secured an equipment grant from the U.S. Department of Defense. From April 2021 to July 2023, Dr. Torre was an Associate Research Scientist in the Department of Computer Information Systems and a member of the Center for Cybersecurity Innovation at Texas A&M University-Central Texas. During this period, he achieved several milestones, including serving as Co-Principal Investigator on an NSF-awarded research proposal and another research project funded by a TARC seed grant from the Texas A&M Engineering Experiment Station (TEES). His work on analyzing vulnerabilities in AI-based techniques was selected as a DARPA Riser at the DARPA FORWARD Conference in 2022. Prior to his contributions in the U.S., Dr. Torre was affiliated with the University of Luxembourg, where he engaged in groundbreaking research projects in collaboration with industry partners in the legal and finance sectors. His work on GDPR compliance and AI-assisted approaches for assessing privacy policies received recognition at prominent conferences and in leading journals. Dr. Torre regularly serves on the organizing and program committees of the International Symposium on Software Reliability Engineering (ISSRE) and the International Conference on Software Quality, Reliability, and Security (QRS), as well as satellite events for the Empirical Software Engineering and Measurement Conference (ESEM), the International Conference on Software Engineering (ICSE), and the Automated Software Engineering Conference (ASE). He is also an IEEE and ACM member.
View the full list of publications on Google Scholar.
- D. Torre, A. Chennamaneni, J. Jo, G. Vyas, and B. Sabrsula. Towards Enhancing Privacy-Preservation of a Federated Learning CNN Intrusion Detection System in IoT: Method and Empirical Study. ACM Transactions on Software Engineering and Methodology (In Press), 2024.
- F. Mesadieu, D. Torre, and A. Chennameneni. Leveraging Deep Reinforcement Learning Technique for Intrusion Detection in SCADA Infrastructure. IEEE Access, 12:63381–63399, 2024.
- D. Torre, F. Mesadieu, and A. Chennamaneni. Deep learning techniques to detect cybersecurity attacks: a systematic mapping study. Empirical Software Engineering, 28(3):1–71, 2023.
- S. Lorenz, S. Stinehoura, A. Chennamaneni, A. Subhani, and D. Torre. IoT forensic analysis: A family of experiments with Amazon Echo devices. Forensic Science International: Digital Investigation, 45:301541, 2023.
- D. Torre, A. Chennamaneni, and A. Rodriguez. Privacy-Preservation Techniques for IoT Devices: A Systematic Mapping Study. IEEE Access, 11:16323–16345, 2023.
- D. Torre, Y. Labiche, M. Genero, and M. Elaasar. How consistency is handled in model-driven software engineering and uml: an expert opinion survey. Software Quality Journal, 31(1):1–54, 2023.
- D. Torre, M. Alferez, G.Soltana, M. Sabetzadeh, and L. C. Briand. Modeling data protection and privacy: application and experience with GDPR. Software and Systems Modeling, 20(6):2071–2087, 2021.
- A. Veizaga, M. Alferez, D. Torre, M. Sabetzadeh, and L. C. Briand. On systematically building a controlled natural language for functional requirements. Empirical Software Engineering, 26(4):79, 2021.
- O. Amaral, S. Abualhaija, D. Torre, M. Sabetzadeh, and L. Briand. AI-enabled automation for completeness checking of privacy policies. IEEE Transactions on Software Engineering, 48(11):4647–4674, 2021.
- D. Torre, Y. Labiche, M. Genero, and M. Elaasar. A systematic identification of consistency rules for UML diagrams. Journal of Systems and Software, 144:121–142, 2018.