Projects per year
Organisation profile
Organisation profile
Research in Computer Science at the University of Hertfordshire has been recognised as excellent in REF 2021, with 90% of the research submitted and all of the research impact rated as internationally excellent or world leading.
The University of Hertfordshire provides a very stimulating environment, offering a large number of specialised and interdisciplinary seminars as well as general training and researcher development opportunities.
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Dive into the research topics where Department of Computer Science is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.
Collaborations and top research areas from the last five years
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Profiles
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Human-Robot Interaction – Best practices and methods
Holthaus, P. (PI)
UKRI - UK Network for Robotics and Autonomous Systems (UK-RAS)
1/07/25 → 30/06/26
Project: Research
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Drug efficacy prediction by using machine learning techniques
Lione, L. (PI) & Helian, N. (CoPI)
19/05/25 → 16/09/25
Project: Research
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KTP: Leveraging large language models securely for B2B activities
Chen, L. (PI) & Zheng, Y. (CoI)
4/11/24 → 3/11/26
Project: Research
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Robotic Cognitive Behavioural Therapy: rCBT
Samani, H., Zaraki, A., Davies, D.-R. & Fernando, O. N. N., 25 Dec 2025, (E-pub ahead of print) Social Robotics - 16th International Conference, ICSR + BioMed 2024, Proceedings. Ge, S. S., Luo, Z., Wang, Y., Samani, H., Ji, R. & He, H. (eds.). Singapore: Springer Nature , Vol. 14916. p. 133-142 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14916 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Citation (Scopus) -
Preventing and Detecting Malware in Smart Environments. The Smart Home Case
Kulkarni, S., Mylonas, A. & Vidalis, S., 5 Jul 2025, (E-pub ahead of print) Malware: Handbook of Prevention and Detection. Gritzalis, D., Choo, K.-K. R. & Patsakis, C. (eds.). Springer Nature Switzerland, Vol. 91. p. 395-410 16 p. (Advances in Information Security; vol. 91).Research output: Chapter in Book/Report/Conference proceeding › Chapter
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Deep learning meets marine biology: Optimized fused features and LIME-driven insights for automated plankton classification
Hassan, M., Salbitani, G., Carfagna, S. & Khan, J. A., 30 Jun 2025, In: Computers in Biology and Medicine. 192, Part A, p. 1-19 19 p., 110273.Research output: Contribution to journal › Article › peer-review
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