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Staff Research Interests

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 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: (opens in a new window)Agent Factory (1996-2010) and (opens in a new window)ASTRA (2010+). A list of my publications can be found on my (opens in a new window)Google Scholar profile.

Currently, I am a Work Package leader for the (opens in a new window)Crop OptimisatioN through Sensing, Understanding and viSualisation (CONSUS) project, a €14.7M strategic partnership programme jointly funded by (opens in a new window)Science Foundation Ireland (SFI) and (opens in a new window)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:

  • User Experience: I am developing new techniques to understand the experience of agency when interacting with novel technologies, including intelligent and on-body interfaces.
  • Health technologies: I have projects investigating the use of games and mobile devices in mental health interventions and lead the user-centred design activities in two large health technology projects, SPHERE and the IEU.
  • Crowdsourcing and information visualisation: Other projects are investigating crowdsourcing and visualisation to support environmental activism and safety critical navigational tasks.
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: (opens in a new window)Google Scholar Profile

Recent Projects

Older Projects

  • Energy-Efficiency Applications
    • Energy price forecasting for cost-aware scheduling design (Opt4Smartcities@CP13, CP12, Elsevier14)
  • Extracting and Exploiting Binary Relationships Graphs (aka ontologies)
    • WordNet/Yago (knowledge graphs), Naga (graph search) (PKDD06, KDD06, ICDE08)
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. 

(opens in a new window)CDVT/AD Tool for Formal Verification of Security Protocols 

(opens in a new window)Crytpographic-Procotol Development and Verification Tool with Attack Detection (CDVT/AD)  is an automated system implementing a (opens in a new window)modal logic of knowledge and an(opens in a new window) 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 (opens in a new window)[1]. Furthermore, this tool successfully verified a large and various set of security protocols (opens in a new window)[1], (opens in a new window)[2], (opens in a new window)[3], (opens in a new window)[4], (opens in a new window)[5] .               

How to use CDVT/AD Tool: 

Download both files ((opens in a new window)CDVT. exe and (opens in a new window)qt-mt310.dll ) and save them in the same folder. To use CDVT/AD tool run the executable CDVT.exe.

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) - (opens in a new window)p(opens in a new window)aper that details the language of CDVT/AD tool and demonstrates its applicatio(opens in a new window)n 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:
1. Initial assumptions (conditions that hold before the protocol starts);
2. Protocol steps (the messages exchanged between the principals);
3. Protocol goals (conditions that are expected to hold if the protocol terminates successfully).

(opens in a new window)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  

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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. Madhusanka Liyanage   5G/6G, Blockchain, Network security, Virtual Networks, Security Protocols, Software Defined Networking (SDN), Internet of Things (IoT), Multi-access Edge Computing (MEC) 
Dr Hadi Tabatabaee Malazi   My research is centered on Edge-Cloud systems, including Multi-Access/Mobile Edge Computing, Mobile Cloud Computing, Fog Computing, and the Internet of Things (IoT). My primary focus is on sustainable computing practices and efficient service orchestration within these distributed systems. I am passionate about applications in Smart Cities, Smart Transportation Networks, and Advanced Health 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
the (opens in a new window)Dublin dashboard project seeks to provide citizens, government workers and companies with real-time information, urban indicator and benchmarking data, and other forms of data about all aspects of the city - transport, environment, economy, housing, culture, population, health, etc. - through a series of interactive graphs, maps and apps. 
 

Dubsim - simulating traffic in the city
this research project developed a micro-simulation of urban traffic flows within a large scale scenario implemented for the greater Dublin region in Ireland. Traditionally, the data available for traffic simulations come from a population census and dedicated road surveys which only partly cover shopping, leisure or recreational trips. To account for the latter, this project exploits the digital footprints of city inhabitants on services such as twitter and foursquare to tune the traffic simulation. 
 

Geovisual analysis of movement data 
recent technological advances have increased the quantity of movement data being recorded. While valuable knowledge can be gained by analysing such data, its sheer volume creates challenges.  Geovisual analytics, which helps the human cognition process by using tools to reason about data, offers powerful techniques to resolve these challenges. This project developed a new Geovisual analytics environment for exploring movement trajectories, which provides visualisation interfaces, based on the classic space-time cube.  

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 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 (opens in a new window)Computational Biology / (opens in a new window)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 (opens in a new window)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 ResearchNature-Inspired Computing and Machine Learning, and their application on Cloud ComputingSoftware 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.

UCD School of Computer Science

University College Dublin, Belfield, Dublin 4, Ireland, D04 V1W8.
T: +353 1 716 2483 | E: computerscience@ucd.ie | Location Map(opens in a new window)