|Dr Deepak Ajwani||
My research interests lie at the confluence of algorithms and data-structures (with a focus on scalable graph algorithms), algorithm engineering, semantic analysis, combinatorial optimization and machine learning.
|Dr Félix Balado||
Signal Processing & Communications, Multimedia Security (Data Hiding, Robust Hashing, Forensics), Bioinformatics
|Dr Brett Becker||
Computer Science Education, High Performance Computing, Parallel and Distributed Computing, Heterogeneous Computing
|Dr Julie Berndsen||
Computational Linguistics, Speech Technology, Linguistic Information Discovery
|Dr Michela Bertolotto||
Geographical information systems, spatial data handling, spatial information science
|Dr Chris Bleakley||
Computational Sensing, Indoor Positioning Systems, Networked Embedded Systems, Computer Architecture
|Dr Abey Campbell||
Augmented Reality, Multi-Agent Systems, Human-Computer Interaction cc
|Dr Joe Carthy||
Cybercrime Investigation and Forensic Computing, Intelligent Information Retrieval, Incident Analysis, Incident Report Retrieval, Lexical Chaining for Topic Tracking and Detection and News Story Segmentation.
|Dr Arthur Cater||
Artificial Intelligence: Computer Go. Computational Linguistics: Compound Nouns
|Dr Simon Caton||
My areas of research reside within the domains of Social Media Mining, Social Computing, Big Data, Machine Learning, and Scalable Analytics.
I am currently looking for strong PhD candidates that have interest in pursuing research in these areas as well as applicable related domains. Potential candidates should outline their motivations for pursuing a research career, comprehensively outline the area(s) of work they would like to explore including expected outcomes, and describe any prior research experience (e.g. if you have undertaken a Bachelors/Masters thesis).
|Dr Rem Collier||
My main research interests lie in the area of Multi-Agent Systems, in particular Agent-Oriented Software Engineering / Programming. The main output of my research work has been the development of a number of Agent Languages / Toolkits, including: Agent Factory (1996-2010) and ASTRA (2010+). A list of my publications can be found on my Google Scholar profile.
Currently, I am a Work Package leader for the Crop OptimisatioN through Sensing, Understanding and viSualisation (CONSUS) project, a €14.7M strategic partnership programme jointly funded by Science Foundation Ireland (SFI) and Origin Enterprises PLC.
|Dr Fintan Costello||
Cognitive Science, Categorisation, Classification, Natural language comprehension and production, Artificial Intelligence, bioinformatics
|Dr David Coyle||
I work mainly in Human Computer Interaction. The overall goal of my research is to design systems that help to address important societal challenges, in particular healthcare and sustainability.
My current work has a strong interdisciplinary focus, with several broad themes:
|Dr Fred Cummins||
Speech, Cognitive Science Foundations
Joint speech as found in prayer and protest; Post-cognitive approaches to the foundations of cognition; Temporal patterning in speech production and perception; Speech rhythm; Dynamic modeling within cognitive science; Gesture, Gaze and Blinking; Speech rate; Conversational interaction; Individual and social cognition; Collective experience. Relation between latter-day approaches to Cognitive Science and recurrent themes in Eastern Religious Philosophy.
|Dr Pádraig Cunningham||
Machine Learning, Data Mining of Multimedia Data, Case-Based Reasoning, Kernel Methods, Real-time Analytics.
|Mr Damian Dalton||
Parallel Processing, Logic design and synthesis, VHDL Verilog; Testing and verification of hardware.
|Dr Soumyabrata Dev|
|Dr Ruihai Dong||
Research Interests: Recommender Systems, Data Analytics, Deep Learning and Machine Learning.
|Dr Brian MacNamee||
My research focuses on machine learning, predictive analytics, and data visualisation. I am especially interested in the confluence of these different topics, and the opportunities they present for human-in-the-loop machine learning.
|Mr John Dunnion||
Intelligent Information Retrieval; Computational Linguistics; Machine Learning.
|Dr Pavel Gladyshev||
Digital Forensics, Cybercrime Investigation, Information Systems Security
|Dr Fatemeh Golpayegani|
|Dr Derek Greene||
Machine learning: Development of novel cluster analysis and dimensionality reduction algorithms, with a particular focus on their application in text mining tasks.
Network analysis: Development and application of clustering and community finding algorithms to dynamic social networks.
Social media analytics: Using data mining and visualisation to explore trends and behaviours in online social media platforms. This has included work on topic modelling, sentiment analysis, content curation, and user recommendation systems.
Digital humanities: Application of network analysis and text mining techniques to explore patterns in literary fiction, in collaboration with the UCD School of English.
|Dr Andrew Hines||
Speech, audio and video signal processing, spatial audio, hearing models, machine learning for computational quality models, cryptosystems.
|Dr Neil Hurley||
Data Analytics, Social network analysis, Recommender systems. Data hiding, digital watermarking, fingerprinting. High-performance computing.
|Dr Georgiana Ifrim||
Research Interests: Machine Learning, Data Mining, Information Extraction, Information Retrieval, AI
Publications: Google Scholar Profile
|Dr Anca Jurcut||
Research Interests: Network Security, Security Protocols Design & Analysis, Automated Techniques for Formal Verification, Cryptography, Security for Internet of Things , Blockchain Technologies, Mathematical Modelling
My research focus on network and information security, security for internet of things (IoT), applications of blockchain technologies, security protocols, formal verification techniques and mathematical modelling.
Some of the key contributions of my research include: (i) development of a novel logic-based technique for the formal verification of protocols; (ii) design and implementation of an automated tool (CDVT/AD: Crytpographic-Procotol Development and Verification Tool with Attack Detection) for the formal analysis and design validation of security protocols; (iii) discovery of several hitherto unknown protocol design flaws and the publication of new verifiably correct protocols; (iv) development and publication of a new set of design guidelines to guarantee protocol robustness against attacks.
Crytpographic-Procotol Development and Verification Tool with Attack Detection (CDVT/AD) is an automated system implementing a modal logic of knowledge and an attack detection theory. Hence, CDVT/AD tool can analyse both:
(a) the evolution of knowledge and belief during a protocol execution and therefore it is useful in addressing issues of both security and trust and
(b) the design vulnerabilities of a protocol and therefore it is useful for the detection of freshness, interleaving session and man-in-the-middle attacks.
Additionally, another benefit of using CDVT/AD tool is that this verification technique is very efficient in terms of memory requirements and execution times (i.e. milliseconds) required for protocol verification . Furthermore, this tool successfully verified a large and various set of security protocols , , , ,  .
How to use CDVT/AD Tool:
Prior to the automated verifi cation the protocol must be formalized, i.e. translated into the language of the tool (i.e.Protocol Specification Language (PSL) - paper that details the language of CDVT/AD tool and demonstrates its application by demonstrating the use of CDVT/AD tool, finding weaknesses in the protocol, and correcting the design of the verified protocol)
A formalized protocol consists of three components:
Sample Specification File: Contains the formalisation into the language of the CDVT_AD tool of Andrew Secure RPC protocol.
The CDVT/AD tool applies the axioms and rules of the implemented logic of knowledge in an attempt to derive the protocol goals as a logical consequence of the initial assumptions and the protocol steps. If such a derivation exists, the verifi cation is successful and the verifi ed protocol can be considered secure within the scope of the logic.
|Dr Mark Keane||
Cognitive Science, Analogy, Similarity, Cognitive Evolution.
|Dr Tahar Kechadi||
|Dr Alexey Lastovetsky||
Heterogeneous Computing; Parallel and Distributed Computing; High Performance Computing; Grid Computing.
|Dr Aonghus Lawlor||
I work on a variety of different areas from recommender systems, sentiment analysis, urban mobility, social network analysis.
|Dr Nhien-An Le-Khac||
Cyber Security, Cybercrime Investigation, Digital Forensics, Cloud Computing, Big Data Analytics, Distributed Data Mining, Adversarial Science
|Dr David Lillis||
Information Retrieval, Digital Forensics, Data Fusion, Text Analytics, Multi-Agent Systems.
|Dr Eleni Mangina||
Applied Artificial Intelligent Systems, Robotics, Remotely Piloted Aircraft Systems and Virtual and Augmented Reality applications in education through simulation.
|Dr Mark Matthews|
|Dr Gavin McArdle||
Selected research projects:
The Dublin Dashboard - city analytics
Dubsim - simulating traffic in the city
Geovisual analysis of movement data
|Dr Lorraine McGinty||
Adaptive Retail, Information Retrieval, User Profiling, Recommender Systems, Case-Based Reasoning (CBR),Intelligent User Interfaces, Personalization, Artificial Intelligence, Negotiated Learning.
|Mr Henry B McLoughlin||
Software Engineering; Formal Software Construction Methods; Enterprise Modelling.
|Dr Catherine Mooney||
Machine Learning, Computational Biology, Bioinformatics
|Dr Liam Murphy||
Performance Issues in Computer and Telecommunications Networks; Multimedia Networking; Performance issues in component-oriented software systems.
|Dr John Murphy||
Performance Engineering as applied to telecommunications networks in particular wireless networks, and also applied to software systems including cloud based. Recent research relates to both IoT and security issues in networking and software systems.
|Dr Vivek Nallur||
I have recently started work on Machine Ethics. I am interested in how to implement and verify ethics in autonomous machines. Questions such as what kinds of ethics would autonomous machines agree to among themselves, how would we ensure that individually ethical machines don't combine to produce un-ethical behaviour, are interesting to pose and answer computationally. This is, by nature, an inter-disciplinary thread and I am quite interested in collaborating with folks in the field of philosophy/law/politics etc.
I'm also very interested in complex self-adaptive systems, engineering emergent feedback loops, predicting and controlling emergence in humano-tech systems (where technical systems interact heavily with human desires/abilities), engineering robust systems from non-robust parts.
Multi-Agent Systems (MAS) are my preferred tool for approaching problems in self-adaptation, complexity, emergence, etc. They lend themselves to extensive forms of experimentation: having all agents follow simple rules, implementing complex machine-learning algorithms, investigating the interplay of different algorithms being used at the same time, are all possible with relatively simple conceptual structures. Decoding the end result and teasing out the real factor(s) responsible for a particular behaviour is considerably more difficult :-).
|Dr Mel Ó Cinnéide||
My present research interests centre around refactoring, and especially the use of search-based software engineering in automated refactoring. Related interests include design patterns, softwaremetrics and code smell detection.
|Dr Gregory O'Hare||
Adaptive Information Cluster, Distributed Artificial Intelligence; Multi-Agent Systems; Agent Oriented Programming, Ubiquitous Computing, Pervasive computing, Ambient Intelligence, Autonomic Wireless sensor Networks.
|Dr Michael O'Mahony||
Recommender Systems, ReputationSystems, Web Search, Machine Learning, Opinion Mining and Data Analytics.
|Dr Liliana Pasquale||
My research interests include requirements engineering and adaptive systems. My work has focused on using runtime requirements models to engineer complex systems, including service compositions and multi-tenant services, cyber-physical systems and more generally systems aimed to satisfy their security and privacy requirements and to be forensic-ready.
|Dr Gianluca Pollastri||
Bioinformatics, Protein Structure Prediction, Machine Learning, Neural Networks.
|Dr Sean Russell||
Agent-Oriented Programming, Agent-Oriented Software Engineering, Multi-Agent Systems, Wireless Sensor Networks, Intelligent Transportation Systems, Computer Science Education.
|Dr Colm Ryan||
My primary research interest is Computational Biology / Bioinformatics. I develop methods to analyse large-scale biological datasets and apply these methods to obtain insight into how biological systems function. A particular focus of my work is the development of approaches to understand how mutations in cancer rewire tumour cells (see description here) and the identification of targeted treatments in cancer (see our resource www.cancergd.org). I am a group leader in Systems Biology Ireland and you can read a little more about the biological focus of my work there.
Computational research areas : machine learning | network analysis | data integration
Biological research areas : synthetic lethality | cancer | proteogenomics | genetic interactions | redundancy
|Dr Takfarinas Saber||
Operations Research, Nature-Inspired Computing and Machine Learning, and their application on Cloud Computing, Software Engineering and Testing, and Communication Network Systems.
|Dr Mark Scanlon|
|Dr Guénolé Silvestre||
His present research activities lie in the area of digital communications, data-hiding and signal processing.
|Dr Anthony Ventresque||
Designing, Engineering and Testing of complex software applications: mobile and distributed (e.g., in the Cloud and on smartphones), using AI components (e.g., chatbots, augmented/virtual reality), processing large quantities of data (big data, urban transportation).