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.

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)

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:
  • TCSS 142: Programming Principles
  • TCSS 455: Introduction to Machine Learning
• Spring 2025:
  • TCSS 142: Programming Principles
• Summer 2025 (upcoming):
  • TCSS 455: Introduction to Machine Learning

The Software Engineering for Secure AI-based Systems (SESAIS) Research Lab, led by Dr. Torre at the University of Washington Tacoma, focuses on enhancing the security, reliability, and trustworthiness of AI-driven software systems. Our research emphasizes critical areas including autonomous systems such as drones and IoT devices, addressing vulnerabilities through innovative cybersecurity techniques. By collaborating with leading academic institutions, industry partners, and government agencies, SESAIS aims to solve emerging cybersecurity challenges, paving the way for robust, resilient, and secure technologies in increasingly interconnected environments.

Research Area

• AI-Driven Cybersecurity: Developing AI-powered Intrusion Detection Systems to identify and mitigate cyber threats in autonomous systems.
• Privacy-Preserving Machine Learning: Enhancing federated learning techniques to ensure data privacy while maintaining robust performance in intrusion detection systems.
• Model-Driven Engineering: Utilizing model-based approaches to improve the design and analysis of complex software systems, ensuring consistency and reliability.

Students Involvement

The SESAIS Lab actively engages students in cutting-edge research projects. I am seeking highly motivated students to join our research group through the Ph.D. program in Computer Science and Systems at the University of Washington Tacoma. Ideal candidates should hold a bachelor's degree and have a strong interest in AI-driven cybersecurity research. If you are interested, please email me your CV and a brief research statement. Additionally, motivated undergraduate and master's students at UW Tacoma are warmly invited to participate in ongoing research projects under my supervision.

CURRENT STUDENTS:

Kannika Armstrong, Master CSS. Research Topic: Optimizing Performance and Efficiency of Lattice-Based Post-Quantum Cryptography Algorithms in Resource-Constrained UAV Environments.

Ruslan Ivanovich Nurimbetov, Master CSS. Research Topic: Federated Learning Techniques to Enhance Security in UAVs.

Jacob Klymenko, Undergraduate CSS. Research Topic: Building a Dataset for Cybersecurity Research on Autonomous Drones.

Faculty Collaboration

Below is a list of faculty members with whom there is ongoing academic collaboration:

Davide Fucci, Associate Professor, Blekinge Institute of Technology, Sweden.

Mohammad Jasim, Assistant Professor, University of Washington Tacoma, USA.

Claudio Menghi, Asssociate Professor, University of Bergamo, Italy.

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, 34(2), 2025.
• 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

CONTACT

Email: dctorre@uw.edu

Office: Milgard Hall (MLG) 221.8

Phone: 253-692-5548