Dr. Alejandro Guerra Manzanares is an assistant professor (lecturer) at the School of Computer Science (CS) at the University of Nottingham, Ningbo, China (UNNC) since October 2024. Before joining UNNC, Alejandro was a postdoctoral research associate at the Clinical AI Lab at New York University, Abu Dhabi, from 2023 to 2024, where he focused on multimodal learning, federated learning and machine learning for healthcare.

Alejandro holds a BA in Criminology from the Autonomous University of Barcelona (UAB, Spain) and a BS in ICT Engineering from the Polytechnic University of Catalonia (UPC, Spain). In 2018, he obtained an MSc in Cybersecurity (specializing in Digital Forensics) from Tallinn University of Technology (TalTech, Estonia) and University of Tartu, and he earned a Ph.D. in Information and Communication Technology / Computer Science from TalTech in 2022. His dissertation focused on the application of machine learning to cybersecurity problems, specifically the detection and characterization of evolving threats in mobile systems and IoT networks.

Alejandro's career has mainly been in academia, complemented by a short period in the industry as a machine learning engineer with the mobile research team at MalwareBytes, during his doctoral studies.

He is passionate about research and is currently seeking dedicated and motivated Ph.D. candidates. He is also open to research collaborations in fundamental machine learning and cybersecurity, as well as at the intersection of machine learning, cybersecurity, and healthcare, including any related topics (see Research Interests below).

Dr. Alejandro Guerra Manzanares is seeking for MRes and PhD students, and scholarship can be provided for excellent PhD students. If you are interested in pursuing a Master's or Ph.D. under his supervision or engaging in collaborative research, please feel free to reach out to him at  alejandro.guerra@nottingham.edu.cn

Alejandro's research interests encompass a broad range of topics, including machine learning, cybersecurity, and healthcare, with a focus on the innovative application of machine learning to solve real-world problems.

His primary research interests include (in no particular order):

• Deep learning
• Digital forensics (mobile, system forensics)
• Cybersecurity (systems security, network security)
• Computer vision
• Multimodal machine learning
• Machine learning for healthcare
• Machine learning for cybersecurity
• Explainable AI (XAI)
• AI robustness and concept drift
• Adversarial machine learning and machine learning security
• Privacy-preserving machine learning, federated learning
• Active learning
• Generative AI (LLMs)

For an updated list of publications, please check [Here]

- General Co-Chair: International Conference on Artificial Intelligence for Cyber Security (AICSEC), 2023, Bratislava, Slovakia

- External Reviewer: Internet of Things (IEEE), Future Generation Computer Systems (Elsevier), Computers & Security (Elsevier), Computer Networks (Elsevier), Forensic Science International: Digital Investigation (Elsevier), Journal of Big Data (Springer Nature), IEEE International Conference on Joint Neural Networks (IJCNN).

- Invited speaker: BSides Conference (Tallinn, 2022), CyberChess Symposium (Latvia, 2023)

I have experience teaching the following subjects at the Master’s level: Machine Learning, Data Mining, and Mobile Phone Forensics.

For the academic year 2025/2026, I will be teaching the following modules:

- Computer Security (COMP3052)

- Systems and Architectures (COMP1047, computer networks part)