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The Intelligent Data Analytics (IDA) research team draws on new advances in AI to develop intelligent algorithms that can process and analyse complex data from diverse sources, such as visual, textual, and physiological data. By exploring new AI concepts and techniques within areas such as Deep Learning, Computer Vision, and Natural Language Processing, the team aims to extract meaningful insights from large datasets, deciphering complex data patterns and relationships that would be challenging or impossible for humans to identify manually. Their research spans several domains, applying these AI-driven methods to real-world problems such as Healthcare, Finance, and Manufacturing, where understanding such data trends is essential for informed decision-making.
The team’s exploration of Brain-Computer Interfaces (BCI) further enhances their capabilities, focusing on technologies that enable direct communication between the brain and external devices. By analysing neural signals, they develop algorithms capable of interpreting brain activity in real-time, with potential applications in human-computer interaction, assistive technologies, and neurorehabilitation.
In addition, the team conducts research in Extended Reality (XR) technologies, including Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). By integrating AI with XR, the IDA team develops immersive, intelligent systems capable of responding to user actions in real-time, thus enabling more dynamic and adaptive environments. This area of research is particularly impactful in fields such as education, skills, and healthcare, where interactive and responsive systems can significantly enhance user experiences.
By combining the strengths of new AI algorithmic development, with advancements in BCI and XR, the IDA research team is pushing the boundaries of intelligent systems.
Deputy Head of the School of Computing, Engineering and Intelligent Systems
Dr Bryan Gardiner
Deputy Head of the School of Computing, Engineering and Intelligent Systems
Dr Bryan Gardiner received a first class honours degree in Electronics and Computer Systems in 2006, and a Ph.D. degree from Ulster University in 2010. Bryan is a Reader in Computer Science and Associate Head of the School of Computing, Engineering and Intelligent Systems at Ulster. A fellow of the HEA, he is also the Research Lead for the Intelligent Data Analytics team within the Intelligent Systems Research Centre.
His research interests are primarily in Data Analytics, with a keen focus on Computer Vision. His research is currently supported by funding from MRC, HSCNI and Interreg NWE. He has undertaken a number of technology commercialisation and knowledge exchange projects funded via Innovate UK, Invest NI and InterTradeIreland.
Bryan is a member of the IEEE UKRI society, IEEE Signal Processing Society (SPS), Irish Pattern Recognition & Classification Society (IPRCS), International Association of Pattern Recognition (IAPR), British Machine Vision Association (BMVA), and affiliate member of IEEE Computational Imaging Special Interest Group.
A Guest Editor of MDPI Remote Sensing Journal, he is also a member of a number of Programme Committees, such as: the International Conference on Image Processing Theory, Tools and Applications; the Artificial Intelligence & Cognitive Systems conference; the Irish Machine Vision Image Processing Conference, and has served as a reviewer for several international conferences and journals.
Senior Lecturer in Computer Science
Dr James Connolly
Senior Lecturer in Computer Science
Senior Lecturer in Mathematics
Dr William Smyth
Senior Lecturer in Mathematics
Lecturer in Data Analytics
Dr Karl McCreadie
Lecturer in Data Analytics
Lecturer in Computer Science
Dr Xuemei Ding
Lecturer in Computer Science
Lecturer in Data Analytics
Dr Muskaan Singh
Lecturer in Data Analytics
Dr. Muskaan Singh is a Lecturer in Data Analytics at the Intelligent Systems Research Centre (ISRC), within the School of Computing, Engineering and Intelligent Systems, Ulster University (UU) and a member of the cognitive analytics research center (CARL).
Her research interest is centered around Natural language Processing, which includes everything from computational linguistics and fair bits of computer science, software engineering, artificial intelligence, machine learning, deep learning, intelligent systems, with a particular focus on practical applications. She has worked on various projects in collaboration with industry and academia ranging from industrial projects to EU-funded H2020 research framework. She has published at prestigious venues (A* and A-ranked conferences) high-impact conferences/journals in the domain of NLP/ML for Machine Translation (MT), Text/Dialogue Summarization, Sentiment Analysis, Social Media Analytics, Scientific Document Processing and Financial/ Forensic Sciences.
Her team has been awarded with First prize winner in Internation Create Challenge, AI Innovation 9-days Hackathon at IDIAP Switzerland, EVAL4NLP at EMNLP 2021, LT-EDI-2022 at ACL 2022, IWSLT at ACL 222, Creative-Summ at COLING 2022, SMM4H 2022 at COLING 2022, DrugProt at NAACL 2021 and third prize winner in the AI Debater Challenge on Argument Pair Extraction task at NLPCC2021.
She has been awarded the Inclusion and Diversity Grant in EMNLP 2021 for presenting her work on Scholarly Document Processing. GHC scholarship, 2019 to present her work on machine translation in Orlando, Florida. She received best poster award in GHCI, Bengaluru and at Curtin University, Malaysia, 2019.
Before joining UU, Dr. Muskaan was working in Speech and Audio Processing Group, IDIAP Research Institute, Switzerland with affiliation to EPFL. She investigated text extracted from audio calls for ROXANNE (Real time network, text, and speaker analytics for combating organized crime) which was EU funded collaborative research and innovation project with Law Enforcement Agencies (LEAs), aiming to unmask criminal networks and their members as well as to reveal the identity of perpetrators by combining the capabilities of speech/language technologies and visual analysis with network analysis.
Dr. Muskaan pursued her postdoctoral work with the Institute of Formal and Applied Linguistics, Faculty of Mathematics and Physics at Charles University, Czech Republic. She explored summarizing meetings in the form of structured minutes for ELITR project “European Live Translator” supported by the EU under the Horizon 2020 program in collaboration with University of Edinburgh, KIT and Alfaview. Dr. Muskaan was also Invited for talk at AILC Lectures on Computational Linguistics 2021. Rome, Italy for presenting this work.
She also was involved in a data analytics project with UU and AllState In, for incident severity prediction framework supported by UK Research and Innovation Turing AI Fellowship 2021-2025 funded by the Engineering and Physical Sciences Research Council.
She received her Ph.D. from Thapar Institute of Engineering and Technology, India in MT, where she focused on extracting linguistic features from Indian languages and feed into Neural MT for End-to-End Training. She developed a web-service for translation of Sanskrit to Hindi, which provides morphological, syntactic, and semantic analysis at each level of translation deployed on AWS cloud services. In her master as well, she studied MT with project ANUSAARKA, for English to Hindi rule-based translation at IIIT Hyderabad, India.
Lecturer in Data Analytics
Dr Vimal Kumar Dwivedi
Lecturer in Data Analytics
Dr Barry Dillon
Lecturer in Mathematics
Dr. Barry Dillon is a lecturer in mathematics at the Intelligent Systems Research Centre (ISRC) within the School of Computing, Engineering and Intelligent Systems, Ulster University (UU).
With a background in particle physics, his main area of research is on how machine-learning can be used to enhance physics analyses at the Large Hadron Collider (LHC) experiment. Particularly on how these machine-learning techniques can be used to aide in the search for signatures of new particles in the data collected at the LHC.
Barry did his PhD in theoretical physics at the University of Sussex and held postdoctoral positions at the University of Plymouth (UK), the Jožef Stefan Institute (Slovenia), and at the University of Heidelberg (Germany). In this time he has worked on many topics in Beyond the Standard Model (BSM) physics, strong-field QED, particle phenomenology, and machine-learning.
You can view his papers via these links:
Professor of Neurotechnology
Professor Damien Coyle
Professor of Neurotechnology
Damien Coyle, Professor of Neurotechnology, is currently Director of the Intelligent Systems Research Centre and Research Director in the School of Computing, Engineering and Intelligent Systems at Ulster University.
He has published over 130 research papers in areas such as computational intelligence/AI, bio-signal processing, computational neuroscience, neuroimaging, neurotechnology and brain-computer interface (BCI) applications and has won a number of prestigious international awards for his research including the 2008 IEEE Computational Intelligence Society (CIS) Outstanding Doctoral Dissertation Award and the 2011 International Neural Network Society (INNS) Young Investigator of the Year Award. He was an Ulster University Distinguished Research Fellow in 2011, a Royal Academy of Engineering/The Leverhulme Trust Senior Research Fellow in 2013 and a Royal Academy of Engineering Enterprise Fellow in 2016-2017. He is a founding member of the International Brain-Computer Interface Society, a Senior member of the IEEE and chairs the IEEE Computational Intelligence Society (CIS) UKIreland chapter.
Professor Coyle is also CEO of NeuroCONCISE Ltd, the Ulster University spinout company he founded in 2016 to build wearable neurotechnology that non-invasively measures and translates brainwaves into control signals using advanced algorithms to enable people to interact with technology and communicate without moving which has applications in rehabilitation, diagnostics, augmentative and assistive communication devices and entertainment.
