Skip to main content

Research Repository

Advanced Search

Dr Stamos Katsigiannis' Outputs (73)

A study on the impact of different components of a traditional webcam-based 2D gaze tracking algorithm (2025)
Journal Article
Blakey, W., Katsigiannis, S., & Ramzan, N. (in press). A study on the impact of different components of a traditional webcam-based 2D gaze tracking algorithm. IEEE Sensors Journal,

Webcam-based 2D gaze tracking algorithms are lightweight and are becoming increasingly used in the fields of medicine, market research and many others. As they become increasingly used, it becomes vital to break down their components to understand th... Read More about A study on the impact of different components of a traditional webcam-based 2D gaze tracking algorithm.

Human Intracranial EEG Biometric Identification (2025)
Presentation / Conference Contribution
Belay, B., & Katsigiannis, S. (2025, July). Human Intracranial EEG Biometric Identification. Presented at International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC), Copenhagen, Denmark

BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction (2025)
Journal Article
Li, R., Katsigiannis, S., Kim, T.-K., & Shum, H. P. H. (online). BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction. IEEE Transactions on Neural Networks and Learning Systems, https://doi.org/10.1109/TNNLS.2025.3545268

Trajectory prediction allows better decision-making in applications of autonomous vehicles (AVs) or surveillance by predicting the short-term future movement of traffic agents. It is classified into pedestrian or heterogeneous trajectory prediction.... Read More about BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction.

SKDU at De-Factify 4.0: Natural language features for AI-Generated Text-Detection (2025)
Presentation / Conference Contribution
Maviya, S., Arnau-González, P., Arevalillo-Herráez, M., & Katsigiannis, S. (2025, February). SKDU at De-Factify 4.0: Natural language features for AI-Generated Text-Detection. Presented at De-factify 4.0 Workshop at 39th Annual AAAI Conference on Artificial Intelligence, Philadelphia, PA, USA

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction (2025)
Journal Article
Li, R., Qiao, T., Katsigiannis, S., Zhu, Z., & Shum, H. P. (online). Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction. IEEE Transactions on Circuits and Systems for Video Technology, https://doi.org/10.1109/TCSVT.2025.3539522

Pedestrian trajectory prediction aims to forecast future movements based on historical paths. Spatial-temporal (ST) methods often separately model spatial interactions among pedestrians and temporal dependencies of individuals. They overlook the dire... Read More about Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction.

SK_DU Team: Cross-Encoder based Evidence Retrieval and Question Generation with Improved Prompt for the AVeriTeC Shared Task (2024)
Presentation / Conference Contribution
Malviya, S., & Katsigiannis, S. (2024, November). SK_DU Team: Cross-Encoder based Evidence Retrieval and Question Generation with Improved Prompt for the AVeriTeC Shared Task. Presented at 7th Fact Extraction and VERification Workshop (FEVER), Miami, Florida, USA

As part of the AVeriTeC shared task, we developed a pipelined system comprising robust and finely tuned models. Our system integrates advanced techniques for evidence retrieval and question generation, leveraging cross-encoders and large language mod... Read More about SK_DU Team: Cross-Encoder based Evidence Retrieval and Question Generation with Improved Prompt for the AVeriTeC Shared Task.

Evidence Retrieval for Fact Verification using Multi-stage Reranking (2024)
Presentation / Conference Contribution
Malviya, S., & Katsigiannis, S. (2024, November). Evidence Retrieval for Fact Verification using Multi-stage Reranking. Presented at 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), Miami, FL, USA

AGENCY—written evidence (FON0017) for House of Lords Communications and Digital Select Committee inquiry: The future of news: impartiality, trust and technology (2024)
Report
Owens, R., Nijia Zhang, V., Malviya, S., Kalameyets, M., Durrant, A., Elliot, K., Farrand, B., Katsigiannis, S., Neesham, C., & Shi, L. (2024). AGENCY—written evidence (FON0017) for House of Lords Communications and Digital Select Committee inquiry: The future of news: impartiality, trust and technology. House of Lords Communications and Digital Select Committee

AGENCY is a multidisciplinary research consortium combining expertise in computer science (human-computer interaction, natural language processing, cybersecurity, and artificial intelligence), design, law, digital technology ethics, responsible innov... Read More about AGENCY—written evidence (FON0017) for House of Lords Communications and Digital Select Committee inquiry: The future of news: impartiality, trust and technology.

Comparative Study of Face Tracking Algorithms for Remote Photoplethysmography (2024)
Presentation / Conference Contribution
Jayasinghe, J., Katsigiannis, S., & Malasinghe, L. (2023, November). Comparative Study of Face Tracking Algorithms for Remote Photoplethysmography. Presented at International Conference on Electrical, Computer and Energy Technologies (ICECET 2023), Cape Town, South Africa

Remote Photoplethysmography (rPPG) is a non-invasive approach for monitoring Heart Rate (HR) that can be used in various applications in healthcare and biometrics. rPPG measurements acquired using facial videos have become very popular and one of the... Read More about Comparative Study of Face Tracking Algorithms for Remote Photoplethysmography.

Fusing ECG signals and IRT models for task difficulty prediction in computerised educational systems (2023)
Journal Article
Arevalillo-Herráez, M., Katsigiannis, S., Alqahtani, F., & Arnau-González, P. (2023). Fusing ECG signals and IRT models for task difficulty prediction in computerised educational systems. Knowledge-Based Systems, 280, Article 111052. https://doi.org/10.1016/j.knosys.2023.111052

Accurately assessing task difficulty is a critical aspect to achieve adaptation in computer-based educational systems. In real-world scenarios, task difficulty estimation can be personalised for individuals by leveraging Item Respon... Read More about Fusing ECG signals and IRT models for task difficulty prediction in computerised educational systems.

Reimagining AI Governance: a Response by AGENCY to the UK Government's White Paper AI Regulation (2023)
Report
Owens, R., Copilah-Ali, J., Kolomeets, M., Malviya, S., Markeviciute, K., Olabode, S., …Farrand, B. (2023). Reimagining AI Governance: a Response by AGENCY to the UK Government's White Paper AI Regulation. SSRN: AGENCY project

In March 29, 2023, the UK Government released a white paper outlining its plans to implement a pro-innovation approach to Artificial Intelligence (AI) regulation and strengthen the UK's position as a global leader in AI.

As part of the white paper... Read More about Reimagining AI Governance: a Response by AGENCY to the UK Government's White Paper AI Regulation.

AGENCY—written evidence (LLM0028) for House of Lords Communications and Digital Select Committee inquiry: Large language models (2023)
Report
Malviya, S., Owens, R., Copilah-Ali, J., Elliot, K., Farrand, B., Neesham, C., Shi, L., Vlachokyriakos, V., Katsigiannis, S., & van Moorsel, A. (2023). AGENCY—written evidence (LLM0028) for House of Lords Communications and Digital Select Committee inquiry: Large language models. House of Lords Communications and Digital Select Committee

AGENCY is a multidisciplinary research team of academics with expertise in computer science (natural language processing, cybersecurity, artificial intelligence, human-computer interaction), law, business, economics, social sciences and media studies... Read More about AGENCY—written evidence (LLM0028) for House of Lords Communications and Digital Select Committee inquiry: Large language models.

Deep learning for Crack Detection on Masonry Façades using Limited Data and Transfer Learning (2023)
Journal Article
Katsigiannis, S., Seyedzadeh, S., Agapiou, A., & Ramzan, N. (2023). Deep learning for Crack Detection on Masonry Façades using Limited Data and Transfer Learning. Journal of Building Engineering, 76, Article 107105. https://doi.org/10.1016/j.jobe.2023.107105

Crack detection in masonry façades is a crucial task for ensuring the safety and longevity of buildings. However, traditional methods are often time-consuming, expensive, and labour-intensive. In recent years, deep learning techniques have been appli... Read More about Deep learning for Crack Detection on Masonry Façades using Limited Data and Transfer Learning.

Towards Automatic Tutoring of Custom Student-Stated Math Word Problems (2023)
Presentation / Conference Contribution
Arnau-González, P., Serrano-Mamolar, A., Katsigiannis, S., & Arevalillo-Herráez, M. (2023, July). Towards Automatic Tutoring of Custom Student-Stated Math Word Problems. Presented at International Conference on Artificial Intelligence in Education (AIED), Tokyo, Japan

Math Word Problem (MWP) solving for teaching math with Intelligent Tutoring Systems (ITSs) faces a major limitation: ITSs only supervise pre-registered problems, requiring substantial manual effort to add new ones. ITSs cannot assist with student-gen... Read More about Towards Automatic Tutoring of Custom Student-Stated Math Word Problems.

Toward Automatic Tutoring of Math Word Problems in Intelligent Tutoring Systems (2023)
Journal Article
Arnau-González, P., Serrano-Mamolar, A., Katsigiannis, S., Althobaiti, T., & Arevalillo-Herráez, M. (2023). Toward Automatic Tutoring of Math Word Problems in Intelligent Tutoring Systems. IEEE Access, 11, 67030-67039. https://doi.org/10.1109/access.2023.3290478

Math Word Problem (MWP) solving, which involves solving math problems in natural language, is a prevalent approach employed by Intelligent Tutoring Systems (ITS) for teaching mathematics. However, one major drawback of ITS is the complexity of encodi... Read More about Toward Automatic Tutoring of Math Word Problems in Intelligent Tutoring Systems.

Multi-modal lung ultrasound image classification by fusing image-based features and probe information (2022)
Presentation / Conference Contribution
Okolo, G. I., Katsigiannis, S., & Ramzan, N. (2022, November). Multi-modal lung ultrasound image classification by fusing image-based features and probe information. Presented at IEEE International Conference on BioInformatics and BioEngineering (BIBE 2022), Taichung, Taiwan

Lung ultrasound is a widely used portable, cheap, and non-invasive medical imaging technology that can be used to identify various lung pathologies. In this work, we propose a multi-modal approach for lung ultrasound image classification that combine... Read More about Multi-modal lung ultrasound image classification by fusing image-based features and probe information.

Automated Detection of Substance-Use Status and Related Information from Clinical Text (2022)
Journal Article
Alzubi, R., Alzoubi, H., Katsigiannis, S., West, D., & Ramzan, N. (2022). Automated Detection of Substance-Use Status and Related Information from Clinical Text. Sensors, 22(24), Article 9609. https://doi.org/10.3390/s22249609

This study aims to develop and evaluate an automated system for extracting information related to patient substance use (smoking, alcohol, and drugs) from unstructured clinical text (medical discharge records). The authors propose a four-stage system... Read More about Automated Detection of Substance-Use Status and Related Information from Clinical Text.

A Localisation Study of Deep Learning Models for Chest X-ray Image Classification (2022)
Presentation / Conference Contribution
Gascoigne-Burns, J., & Katsigiannis, S. (2022, September). A Localisation Study of Deep Learning Models for Chest X-ray Image Classification. Presented at 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), Ioannina, Greece

Deep learning models have demonstrated superhuman performance in a multitude of image classification tasks, including the classification of chest X-ray images. Despite this, medical professionals are reluctant to embrace these models in clinical sett... Read More about A Localisation Study of Deep Learning Models for Chest X-ray Image Classification.

SOS: Systematic Offensive Stereotyping Bias in Word Embeddings (2022)
Presentation / Conference Contribution
Elsafoury, F., Wilson, S. R., Katsigiannis, S., & Ramzan, N. (2022, October). SOS: Systematic Offensive Stereotyping Bias in Word Embeddings. Presented at 29th International Conference on Computational Linguistics (COLING 2022), Gyeongju, Republic of Korea

Systematic Offensive stereotyping (SOS) in word embeddings could lead to associating marginalised groups with hate speech and profanity, which might lead to blocking and silencing those groups, especially on social media platforms. In this [id=stk]wo... Read More about SOS: Systematic Offensive Stereotyping Bias in Word Embeddings.