role: Supervisors
Dr. Marija Bezbradica
CRT in AI Supervisor
Marija Bezbradica obtained my B.Sc.E.E. from the School of Electrical Engineering, University of Belgrade, Serbia (2007) and MSc in Biomedical Engineering from the same University (2008). Marija then acquired extensive experience in Complex Systems Modelling and Scientific Computing, completing her PhD in the School of Computing in DCU, Ireland (2013). Specifically, the research involved building stochastic models to predict dissolution of complex drug formulations and controlled release of active pharmaceutical substances. Her subsequent postdoctoral research at DCU (2013-2015) included design and implementation of stochastic computational models and predictive methods for pedestrian behaviour, particularly in large, complex urban networks. Marija’s current areas of research, as an Assistant Professor, (2015 – date) remain strongly interdisciplinary and include implementation of computational simulation methods such as cellular automata and agent-based models, predictive and behavioural analytics in software usage, Smart Cities, as well as FinTech and InsurTech areas, drawing on a background in machine learning, applied mathematics, statistics and high performance computing. Marija received national and international funding in domain of retail analytic and Fintech.
OTHER TEAM MEMBERS
Dr. Vladimir Krylov
CRT in AI Supervisor
Discipline: Computer Vision, Statistics
Specialisation: Remote sensing image processing, geolocalisation
ML, AI, DL, CV
Professor Annalina Caputo
CRT in AI Supervisor
Information Retrieval, Natural Language Processing, Recommender Systems
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Dr. Mélanie Bouroche
CRT in AI Supervisor
Mélanie Bouroche graduated from INP Grenoble, France, in 2003, and was awarded an M.Sc. in Computer Science (2003) and a PhD (2008) from Trinity College Dublin.
Mélanie is a lecturer and manager of the Future Cities Research program in the School of Computer Science and Statistics at Trinity College Dublin. She has over 15 year experience in research key programming abstractions for urban-scale reliable context-aware applications, in conjunction with a number of indigenous and multinational companies, as well as public bodies, including Intel Labs, Bell Labs, and Dublin City Council. Her research addresses many aspects of Distributed Systems, in particular Middleware for Future Cities, Participatory Sensing and Connected Vehicle Coordination.
Professor Vinny Cahill
CRT in AI Supervisor
Prof Vinny Cahill holds a Personal Chair in Computer Science at Trinity College Dublin. Prof Cahill has previously served as the University’s Dean & Vice-President for Research, Dean of the Faculty of Engineering, Mathematics and Science – one of the University’s three faculties, and in a number of other roles.
Prof. Cahill’s research addresses many aspects of distributed systems, in particular, middleware and programming models for mobile, ubiquitous and autonomic computing with application to optimization of urban resource usage and service delivery in order to improve the quality of life and sustainability of cities.
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Professor Owen Conlon
Associate Professor
Prof. Owen Conlan is a Full Professor in Computer Science in the School of Computer Science and Statistics and is the Co-director of the Trinity Centre for Digital Humanities. He is recognised as an international leader in the area of personalisation research. The vision that underpins his research is: advancing knowledge-based, visualisation and artificial intelligence techniques to support improved human cognition, engagement and understanding of complex information. His current work focusses on proactive personalisation, where autonomous intelligent digital assistants act on user’s behalf. He has brought leadership to field of personalisation (e.g. General Chair of UMAP 2015 and Hypertext 2021) and has made a significant scholarly contribution to the field (190+ publications; h-index of 29; ~3300 citations). He has secured approximately €10.8m in competitive research and industry funding as principal investigator and has an extensive network of international multi-disciplinary collaborators through the European Commission projects he has coordinated and in which he performed both coordinator and scientific leadership roles. Owen is also one of seven founding PIs of ADAPT, a €50 million (co-funded by 25+ industry partners and Science Foundation Ireland) Global Centre of Excellence for Digital Content Technology, led from Trinity College Dublin. He is also a co-applicant, co-PI and Strand Leader of the Science Foundation Ireland ADAPT research centre and in the recently awarded ADAPT II proposal (securing a further €32 million in funding for the centre from 2021 to 2026). Owen leads the Digitally Enhanced Engagement strand in ADAPT which is underpinned by his research vision for personalised proactive agency, with a responsibility for a budget of over €5 million (representing a third of the centre’s research platform budget). He supports a team of twelve researchers and has successfully supervised seventeen PhD candidates to completion. Owen also has significant experience collaborating with industry partners, having worked with Huawei, Mazda, Deutsche Bank, and over 15 other industry partners. Owen has also brought his research to market having supported three successful spin-out, which were underpinned by three international patent applications.
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Dr. Derek Bridge
Co-Director
Dr. Derek Bridge has nearly two decades’ of experience in the fields of recommender systems, personalisation, and machine learning. He is one of the founders of the ACM Conference in Recommender Systems and co-chaired it in 2008. His research covers many topics within recommender systems, most notably case-based recommenders, conversational recommenders, group recommendations, diversity and serendipity, and explanations.
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Professor Tiziana Margaria
Co-Director
Prof. Margaria is Chair of Software Systems at the University of Limerick (Ireland), where she is currently Head of the Department of Computer Science and Information Systems. Her career funding totals over €80 million, over €18m of which to the own institution. Her broad research experience in the development and use of formal methods for high assurance systems, in particular concerning functional verification, reliability, and compliance of complex heterogeneous systems.
OTHER TEAM MEMBERS
Dr. Ivana Dusparic
Co-Director
Ivana Dusparic is an Ussher Assistant Professor in Future Cities and the Internet of Things in the School of Computer Science and Statistics, a post she took up in 2016. She has obtained a BSc from La Roche College, Pittsburgh, USA in 2001, and an MSc and PhD from TCD in 2005 and 2010, respectively.
Her research expertise is the development of new artificial intelligence algorithms, and specifically reinforcement learning, for optimization of large-scale infrastructures. She has authored numerous peer-reviewed articles in the areas of reinforcement learning agents, multi-agent systems, intelligent mobility, and future communication networks.
Her research has been funded through a number of SFI and IRC initiatives, as well as by the industry partners. She is currently TCD lead of the SFI Centre for Research Training in AI, Principal Investigator of the Smart Networking in the Era of AI collaboration between Trinity College Dublin and Tsinghua University, and a Funded Investigator at Enable/CONNECT Research Centre.
She is active both nationally and internationally on promoting AI-enabled sustainability. She is a member of the management committee of the European COST network on Wider Impacts of Autonomous Vehicles, a member of the Royal Irish Academy’s Computer Science and Engineering Committee, and a member of the steering committee of Future Cities: The Trinity Center for Smart and Sustainable Cities.
OTHER TEAM MEMBERS
Dr. Suzanne Little
Co-Director
Dr. Suzanne Little (Co-Director, DCU). Dr. Little is an assistant professor in the School of Computing at Dublin City University and an SFI Funded Investigator in the Insight Centre for Data Analytics. Her research interests are in the area of multimedia semantics and she uses tools from artificial intelligence, machine learning, computer vision and information retrieval to improve methods for content-based media analytics.