BIOGRAPHY

Dr. Torre is a tenure-track Assistant Professor of Computer Science and Systems at the School of Engineering and Technology, University of Washington Tacoma, WA, USA. He holds a Ph.D. in Electrical and Computer Engineering from Carleton University, Canada (2018), an M.Sc. in Advanced Informatics Technologies from the University of Castilla-La Mancha, Spain (2011), and a B.Sc. in Computer Science from the University of Bari Aldo Moro, Italy (2009). Before joining UW Tacoma, Dr. Torre served as an Assistant Professor of Software Engineering at St. Mary’s University in San Antonio, TX, and as an Associate Research Scientist at Texas A&M University-Central Texas, where he collaborated with organizations such as the Air Force Research Laboratory and the Department of Homeland Security. Dr. Torre has led and contributed to numerous research projects, including advancements in AI-enabled cybersecurity systems for autonomous vehicles, privacy-preserving federated learning in IoT, and model-driven software engineering. He has co-authored over 20 peer-reviewed journal and conference papers and holds a strong focus on applied research that bridges academia and industry. His research interests include Software Engineering, Artificial Intelligence, Cybersecurity, Model-Driven Engineering, and Empirical Studies. Dr. Torre is an active member of ACM and IEEE, with a proven record of publishing in and reviewing for prestigious journals such as IEEE Transactions on Software Engineering, ACM Transactions on Software Engineering and Methodology, and Empirical Software Engineering. He emphasizes student engagement in his research, mentoring the next generation of engineers to address complex challenges in the field of Software Engineering.

RESEARCH

Dr. Torre research focuses on the intersection of Software Engineering, Artificial Intelligence, Cybersecurity, Model-Driven Engineering, and Empirical Studies. At the University of Washington Tacoma, his work centers on addressing cybersecurity challenges in AI-driven autonomous systems, particularly vehicles such as drones. His research tackles vulnerabilities in both networked and isolated environments, aiming to strengthen the resilience of these systems against cyber-physical attacks. By conducting real-world experiments and implementing AI-powered Intrusion Detection Systems, Dr. Torre seeks to establish robust benchmarks for protecting these transformative technologies.

PROSPECTIVE STUDENTS

I am seeking highly motivated students to join the Ph.D. program in Computer Science and Systems at the University of Washington Tacoma. Candidates should hold a bachelor's degree and have a strong interest in research. If interested, please email me your CV and a research statement. Additionally, motivated undergraduate and master's students at UW are warmly welcome to participate in research activities under my guidance.

TEACHING

Dr. Torre teaches courses in Computer Science and Software Engineering, including Artificial Intelligence and Programming. His teaching philosophy emphasizes practical applications and fostering critical thinking.

• Autumn 2024:
  • TCSS 142: Programming Principles
  • TCES 203: Programming Practicum
• Winter 2025 (upcoming):
  • TCSS 142: Programming Principles
  • TCSS 455: Introduction to Machine Learning

SELECTED PUBLICATIONS

• 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.

To access all publications, use Google Scholar: Google Scholar Profile

DEGREES

Ph.D. in Electrical and Computer Engineering
Carleton University, Ottawa, Canada (2018)

Master of Science in Advanced Informatics Technologies
University of Castilla-La Mancha, Ciudad Real, Spain (2011)

Bachelor of Science in Computer Science
University of Bari Aldo Moro, Bari, Italy (2009)

CONTACT

Email: dctorre@uw.edu

Office: Milgard Hall (MLG) 221.8

Phone: 253-692-5548