Staff profile

Dr Stamos Katsigiannis is an Assistant Professor in Computer Science at the Department of Computer Science of Durham University. His research interests lie in the fields of bioinformatics, health informatics, affective computing, image analysis, machine learning, image and video quality, and GPU computing.

Before joining Durham, he was a Postdoctoral Research Fellow and a Lecturer at the School of Computing, Engineering and Physical Sciences of the University of the West of Scotland, UK (2016-2020), as well as a junior researcher/PhD candidate at the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens, Greece (2009-2016).

He holds a BSc (Hons.) degree in Informatics and Telecommunications from the National and Kapodistrian University of Athens, Greece, an MSc in Computer Science from the Athens University of Economics and Business, Greece, and a PhD degree in Computer Science from the National and Kapodistrian University of Athens, Greece.

Google Scholar Profile

• Applied machine learning
• Bioinformatics
• Bio-signal processing
• Health informatics
• Affective computing
• Image/video processing
• Image/video quality
• GPU computing

Chapter in book

• Al-Qahtani, M., Katsigiannis, S., & Ramzan, N. (2020). Information Retrieval from Electronic Health Records. In M. A. Imran, R. Ghannam, & Q. H. Abbasi (Eds.), Engineering and technology for healthcare (117-128). Wiley-IEEE Press
• Althobaiti, T., Katsigiannis, S., West, D., Rabah, H., & Ramzan, N. (2020). Machine learning-based affect detection within the context of human-horse interaction. In M. Z. Shakir, & N. Ramzan (Eds.), AI for Emerging Verticals; Human-robot computing, sensing and networking. IET
• Arnau-González, P., Katsigiannis, S., Arevalillo-Herráez, M., & Ramzan, N. (2020). Artificial Intelligence for Affective Computing: An emotion recognition case study. In M. Z. Shakir, & N. Ramzan (Eds.), AI for emerging verticals; human-robot computing, sensing and networking. IET
• Katsigiannis, S., Rabah, H., & Ramzan, N. (2020). A machine learning driven solution to the problem of perceptual video quality metrics. In M. Z. Shakir, & N. Ramzan (Eds.), AI for Emerging Verticals; Human-robot computing, sensing and networking. IET
• Arnau-González, P., Katsigiannis, S., Arevalillo-Herráez, M., & Ramzan, N. (2020). EEG-based biometrics: Effects of template ageing. In M. Z. Shakir, & N. Ramzan (Eds.), AI for Emerging Verticals; Human-robot computing, sensing and networking. IET
• Katsigiannis, S., Ahmad, W., & Ramzan, N. (2019). 5G: Disruption in Media and Entertainment. In Enabling 5G Communication Systems to Support Vertical Industries (179-190). Wiley-IEEE Press. https://doi.org/10.1002/9781119515579.ch8
• Katsigiannis, S., Keramidas, E., & Maroulis, D. (2013). FLBP: Fuzzy Local Binary Patterns. In Local Binary Patterns: New Variants and Applications (149-175). Springer Verlag. https://doi.org/10.1007/978-3-642-39289-4_7
• Katsigiannis, S., Papaioannou, G., & Maroulis, D. (2013). A Real-Time Video Encoding Scheme Based on the Contourlet Transform. In Design and Architectures for Digital Signal Processing. https://doi.org/10.5772/51735

Conference Paper

• 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
• 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
• 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
• 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
• Li, R., Katsigiannis, S., & Shum, H. P. (2022, October). Multiclass-SGCN: Sparse Graph-based Trajectory Prediction with Agent Class Embedding. Presented at ICIP 2022: IEEE International Conference in Image Processing, Bordeaux, France
• 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
• Wu, Y., Arevalillo-Herráez, M., Katsigiannis, S., & Ramzan, N. (2022, July). On the benefits of using Hidden Markov Models to predict emotions. Presented at ACM Conference on User Modeling, Adaptation and Personalization (UMAP), Barcelona
• 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
• 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
• Elsafoury, F., Katsigiannis, S., Wilson, S., & Ramzan, N. (2021, July). Does BERT pay attention to cyberbullying?. Presented at 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Online
• Katsigiannis, S., Arnau-González, P., Arevalillo-Herráez, M., & Ramzan, N. (2021, July). Single-channel EEG-based subject identification using visual stimuli. Presented at 2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), Online
• Blakey, W. A., Katsigiannis, S., Hajimirza, N., & Ramzan, N. (2020, December). Defining gaze tracking metrics by observing a growing divide between 2D and 3D tracking. Presented at IS&T International Symposium on Electronic Imaging, Burlingame, CA, USA
• Arevalillo-Herráez, M., Chicote-Huete, G., Ferri, F., Ayesh, A., Boticario, J., Katsigiannis, S., Ramzan, N., & Arnau-González, P. (2019, October). On using EEG signals for emotion modeling and biometrics. Presented at 33rd European Simulation and Modelling Conference (ESM), Palma de Mallorca, Spain
• Alqahtani, F., Katsigiannis, S., & Ramzan, N. (2019, December). ECG-based affective computing for difficulty level prediction in Intelligent Tutoring Systems. Presented at 4th International Conference on UK/China Emerging Technologies (UCET), Glasgow, United Kingdom
• Arnau-González, P., Katsigiannis, S., Arevalillo-Herráez, M., & Ramzan, N. (2019, December). Image-Evoked Affect and its Impact on EEG-Based Biometrics. Presented at IEEE International Conference on Image Processing (IEEE ICIP), Taipei, Taiwan
• Alqahtani, F., Katsigiannis, S., & Ramzan, N. (2019, December). On the use of ECG and EMG Signals for Question Difficulty Level Prediction in the Context of Intelligent Tutoring Systems. Presented at 19th IEEE International Conference on Bioinformatics and Bioengineering (IEEE BIBE), Athens, Greece
• Kostopoulou, E., Katsigiannis, S., & Maroulis, D. (2019, December). SpotDSQ: A 2D-Gel Image Analysis Tool for Protein Spot Detection, Segmentation and Quantification. Presented at 19th IEEE International Conference on Bioinformatics and Bioengineering (IEEE BIBE), Athens, Greece
• Althobaiti, T., Katsigiannis, S., West, D., Bronte-Stewart, M., & Ramzan, N. (2018, December). Affect Detection for Human-Horse Interaction. Presented at 21st Saudi Computer Society National Computer Conference (NCC), Riyadh, Saudi Arabia
• Malasinghe, L., Katsigiannis, S., Ramzan, N., & Dahal, K. (2018, December). Remote Heart Rate Extraction Using Microsoft KinectTM v2.0. Presented at 10th International Conference on Bioinformatics and Biomedical Technology (ICBBT), Amsterdam, Netherlands
• Alzahrani, I. R., Ramzan, N., Katsigiannis, S., & Amira, A. (2018, December). Use of Machine Learning for Rate Adaptation in MPEG-DASH for Quality of Experience Improvement. Presented at 5th International Symposium on Data Mining Applications (SDMA), Riyadh, Saudi Arabia
• Alzubi, R., Ramzan, N., Alzoubi, H., & Katsigiannis, S. (2018, December). SNPs-based Hypertension Disease Detection via Machine Learning Techniques. Presented at 24th International Conference on Automation and Computing (ICAC), Newcastle upon Tyne, United Kingdom
• Arnau-González, P., Althobaiti, T., Katsigiannis, S., & Ramzan, N. (2017, December). Perceptual video quality evaluation by means of physiological signals. Presented at 9th International Conference on Quality of Multimedia Experience (QoMEX), Erfurt, Germany
• Kostopoulou, E., Katsigiannis, S., Maroulis, D., Pappa, K., & Anagnou, N. (2015, May). Spot detection in 2D-gel electrophoresis images. Presented at 6th Panhellenic Conference on Biomedical Technology (ΕΛΕΒΙΤ), Athens, Greece
• Katsigiannis, S., Dimitsas, V., & Maroulis, D. (2015, December). A GPU vs CPU performance evaluation of an experimental video compression algorithm. Presented at 7th International Workshop on Quality of Multimedia Experience (QoMEX), Pylos, Greece
• Kostopoulou, E., Katsigiannis, S., Maroulis, D., Pappa, K., & Anagnou, N. (2015, December). A novel approach for accurate 2D-gel image segmentation. Presented at 10th Conference of the Hellenic Society for Computational Biology & Bioinformatics, Athens, Greece
• Kostopoulou, E., Katsigiannis, S., & Maroulis, D. (2015, December). A custom grow-cut based scheme for 2D-gel image segmentation. Presented at 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC), Milan, Italy
• Katsigiannis, S., & Maroulis, D. (2013, December). Parallel computing techniques for performance enhancement of a cDNA microarray gridding algorithm. Presented at IEEE International Symposium on Signal Processing and Information Technology (IEEE ISSPIT), Athens, Greece
• Katsigiannis, S., Maroulis, D., & Papaioannou, G. (2013, December). A GPU based real-time video compression method for video conferencing. Presented at 18th International Conference on Digital Signal Processing (IEEE DSP), Santorini, Greece
• Katsigiannis, S., Zacharia, E., & Maroulis, D. (2013, December). Enhancing the performance of a microarray gridding algorithm via GPU computing techniques. Presented at 13th IEEE International Conference on BioInformatics and BioEngineering (IEEE BIBE), Chania, Greece
• Katsigiannis, S., Papaioannou, G., & Maroulis, D. (2012, December). A contourlet transform based algorithm for real-time video encoding. Presented at SPIE Photonics Europe, Real-Time Image and Video Processing 2012, Brussels, Belgium
• Katsigiannis, S. (2010, October). Contourlet Transform and Support Vector Machines for Image Analysis and Processing. Presented at 1st International Conference for undergraduate and graduate students in Informatics and Related Applications (EUREKA! 2010), Patras, Greece
• Katsigiannis, S., Keramidas, E. G., & Maroulis, D. (2010, December). Contourlet Transform for Texture Representation of Ultrasound Thyroid Images. Presented at 6th IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI 2010), Larnaca, Cyprus

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
• 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
• 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
• 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
• Malasinghe, L., Katsigiannis, S., Dahal, K., & Ramzan, N. (2022). A Comparative Study of Common Steps in Video-based Remote Heart Rate Detection Methods. Expert Systems with Applications, 207, Article 117867. https://doi.org/10.1016/j.eswa.2022.117867
• Okolo, G. I., Katsigiannis, S., & Ramzan, N. (2022). IEViT: An Enhanced Vision Transformer Architecture for Chest X-ray Image Classification. Computer Methods and Programs in Biomedicine, 226, Article 107141. https://doi.org/10.1016/j.cmpb.2022.107141
• Arevalillo-Herráez, M., Segura-García, J., Arnau-González, P., & Katsigiannis, S. (2022). Wrap reduction algorithm for Fringe Projection Profilometry. Optics and Lasers in Engineering, 158, Article 107185. https://doi.org/10.1016/j.optlaseng.2022.107185
• Okolo, G. I., Katsigiannis, S., Althobaiti, T., & Ramzan, N. (2021). On the Use of Deep Learning for Imaging-Based COVID-19 Detection Using Chest X-rays. Sensors, 21(17), Article 5702. https://doi.org/10.3390/s21175702
• Arnau-González, P., Katsigiannis, S., Arevalillo-Herráez, M., & Ramzan, N. (2021). BED: A new dataset for EEG-based biometrics. IEEE Internet of Things Journal, 8(15), 12219-12230. https://doi.org/10.1109/jiot.2021.3061727
• Alqahtani, F., Katsigiannis, S., & Ramzan, N. (2021). Using wearable physiological sensors for affect-aware Intelligent Tutoring Systems. IEEE Sensors Journal, 21(3), 3366-3378. https://doi.org/10.1109/jsen.2020.3023886
• Elsafoury, F., Katsigiannis, S., Pervez, Z., & Ramzan, N. (2021). When the timeline meets the pipeline: A survey on automated cyberbullying detection. IEEE Access, 9, 103541-103563. https://doi.org/10.1109/access.2021.3098979
• Arnau-González, P., Arevalillo-Herráez, M., Katsigiannis, S., & Ramzan, N. (2021). On the influence of affect in EEG-based subject identification. IEEE Transactions on Affective Computing, 12(2), 391-401. https://doi.org/10.1109/taffc.2018.2877986
• Althobaiti, T., Katsigiannis, S., & Ramzan, N. (2020). Triaxial Accelerometer-Based Falls and Activities of Daily Life Detection Using Machine Learning. Sensors, 20(13), Article 3777. https://doi.org/10.3390/s20133777
• Katsigiannis, S., Willis, R., & Ramzan, N. (2019). A QoE and Simulator Sickness Evaluation of a Smart-Exercise-Bike Virtual Reality System via User Feedback and Physiological Signals. IEEE Transactions on Consumer Electronics, 65(1), 119-127. https://doi.org/10.1109/tce.2018.2879065
• Kerdjidj, O., Amira, A., Ghanem, K., Ramzan, N., Katsigiannis, S., & Chouireb, F. (2019). An FPGA implementation of the matching pursuit algorithm for a compressed sensing enabled e-Health monitoring platform. Microprocessors and Microsystems, 67, 131-139. https://doi.org/10.1016/j.micpro.2019.03.007
• Althobaiti, T., Katsigiannis, S., West, D., & Ramzan, N. (2019). Examining Human-Horse Interaction by Means of Affect Recognition via Physiological Signals. IEEE Access, 7, 77857-77867. https://doi.org/10.1109/access.2019.2922037
• Katsigiannis, S., Scovell, J., Ramzan, N., Janowski, L., Corriveau, P., Saad, M. A., & Van Wallendael, G. (2018). Interpreting MOS scores, when can users see a difference? Understanding user experience differences for photo quality. Quality and User Experience, 3(1), Article 6. https://doi.org/10.1007/s41233-018-0019-8
• Katsigiannis, S., & Ramzan, N. (2018). DREAMER: A Database for Emotion Recognition Through EEG and ECG Signals From Wireless Low-cost Off-the-Shelf Devices. IEEE Journal of Biomedical and Health Informatics, 22(1), 98-107. https://doi.org/10.1109/jbhi.2017.2688239
• Katsigiannis, S., Zacharia, E., & Maroulis, D. (2017). MIGS-GPU: Microarray Image Gridding and Segmentation on the GPU. IEEE Journal of Biomedical and Health Informatics, 21(3), 867-874. https://doi.org/10.1109/jbhi.2016.2537922
• Kostopoulou, E., Katsigiannis, S., & Maroulis, D. (2015). 2D-gel spot detection and segmentation based on modified image-aware grow-cut and regional intensity information. Computer Methods and Programs in Biomedicine, 122(1), 26-39. https://doi.org/10.1016/j.cmpb.2015.06.007
• Katsigiannis, S., Zacharia, E., & Maroulis, D. (2015). Grow-Cut Based Automatic cDNA Microarray Image Segmentation. IEEE Transactions on NanoBioscience, 14(1), 138-145. https://doi.org/10.1109/tnb.2014.2369961
• Katsigiannis, S., Keramidas, E., & Maroulis, D. (2010). A Contourlet Transform Feature Extraction Scheme for Ultrasound Thyroid Texture Classification

Other (Digital/Visual Media)

• Katsigiannis, S., Papaioannou, G., & Maroulis, D. (2015). CVC: The Contourlet Video Compression algorithm for real-time applications

Report

• Owens, R., Copilah-Ali, J., Kolomeets, M., Malviya, S., Markeviciute, K., Olabode, S., Spiliotopoulos, T., Wu, H., Zhang, V. N., Coopamootoo, K., Durrant, A., Elliot, K., Katsigiannis, S., Neesham, C., Shi, L., & Farrand, B. (2023). Reimagining AI Governance: a Response by AGENCY to the UK Government's White Paper AI Regulation. SSRN: AGENCY project
• 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