Computing, Digital & Data - Research

School of Computer Science



Research in the School of Computer Science at Grangegorman City Campus focuses on using technology to solve real world problems. The School undertakes a broad range of research which can be categorised under the following research themes:



Intelligent Systems – this theme focuses on researching and using computational intelligent technologies to address real world problems. It covers the areas of artificial intelligence, machine learning, data science and knowledge based systems.



Communication & Language – research in this theme centres on how computers can help facilitate communication among individuals and between humans and computers. It includes areas of natural language processing, robotics, computational linguistics and human computer interaction.



Social Computing – research in this theme considers how technology can address and assist with societal challenges in the areas of health, the environment, security and accessibility. Computer science education, ethics and inclusion is part of this theme and focuses on how computer science is taught at school and university level. This theme also includes research into addressing the gender imbalance and lack of inclusion that currently exists in technology based areas.



School of Enterprise Computing and Digital Transformation



Research groups involving the School of Enterprise Computing and Digital Transformation include:

Computer Science Inclusive

Social Media Research Group



School of Informatics and Cybersecurity



The school prides itself on the range of research led undergraduate and postgraduate programmes it offers. This requires academic staff members that are research active in areas that underpin our programmes and lead to postgraduate research opportunities at MSc and PhD level.



The schools active research areas include:

Cyber Security & Digital Forensics

Biometrics

Design Technologies and Augmented Reality

Data Science, Natural Language Processing and computational linguistics

Artificial Intelligence and Machine Learning

Sign Language Processing

Learning Analytics

Teaching & Learning

High Performance Computing

Sociotechnical studies



The school has a long history of participation and collaboration in national and EU funded research projects and has attracted research funding totalling 4.5 million in the last five years on projects including:



Collaboratory (EI Regional Development Enterprise €2.5M)

Cyber Skills (Partner in HEA HCI (Human Computer Interaction) P3 project €8.5M)

SignON (partner in Horizon2020 project, €5.6M)

DALTAI and SATLE2020 (National Forum for the Enhancement of Teaching and Learning in Higher Education, €289K combined).

CloudStream (EI Commercialisation Fund of €380,000) in partnership with the Performance Engineering Lab, UCD and MDS Gateways

N-Light (Tech Coalition Safe Online Research Fund of €102,000) in partnership with the ISPCC and Hotline.ie

PhD funding from IRC, TU Dublin, IBM, Dell

Numerous funding amounts under 50K from EI Innovation vouchers, SFI Discovery, TU Dublin IMPACT, TU Dublin PG Funds, HEA, etc.

Trustboos: Unifying & Upgrading Certification Capabilities Across Europe



These research areas are supported by the following research groups within the school:



Cyber Security research group - Security Research Group

Data Science research group https://www.applieddatasciencemasters.com/

Natural Language Processing group

Nexus Labs (https://www.hpcnexuslab.ie/)



School of Mathematics & Statistics



Research in the School of Mathematics & Statistics spans pure & applied mathematics, statistics and operations research. Staff are actively engaged in research at the forefront of their fields and the School fosters and supports all forms of scholarship. Research informs all aspects of the Schools’ activities, particularly the teaching, and postgraduate students who are a vital part of the research ethos.



Postgraduate education is fundamental to the activities of the School and postgraduate students are active participants in the research community. The School offers opportunities for postgraduate study in mathematical sciences and statistics towards the degrees of MPhil and PhD on either a part-time or a full-time basis.



Mathematical Sciences Research Group

Research in the School of Mathematics & Statistics is brought together through the Mathematical Sciences Research Group. The group encompasses research across Mathematical Sciences and strongly encourages collaboration between members of the School and external researchers, research centres and industry.



Areas of research activity



Fluid Mechanics:

Prandtl boundary layers; slow viscous flows; rotationally-driven flows; nonlinear water waves; wave-current interactions; fluid flows with vorticity; boundary layers; applications to melt-spinning processes.

Researchers: Nicole Beisiegel; John Butler; Laura Cooke; Chris Hills; Rossen Ivanov

Collaborators: Sustainability & Health



Functional Analysis, Algebra & Geometry:

Finite geometry; combinatorics; coding theory; infinite-dimensional holomorphy; applications of functional analysis; topological & geometric methods in group theory.

Researchers: Milena Venkova; Colum Watt



Mathematical Modelling & Simulation:

Theoretical neuroscience; signal processing; computational statistics; modelling of problems in physics or biotechnology; nonlinear dynamical systems & differential equations; computational finance; numerical analysis.

Researchers: Nicole Beisiegel; John Butler; Dana Mackey; Pierce Ryan

Collaborators: Laura Cooke; Chris Hills; Rossen Ivanov; Sustainability & Health; Physical to Life Sciences



Mathematical Physics:

Quantum field theory in curved space-times; integrable systems and solitons; Lagrangian & Hamiltonian mechanics; high-energy astrophysics; star formation; high-performance computing in mathematical physics; quantum, classical & topological field theory; general relativity & cosmology.

Researchers: Cormac Breen; Rossen Ivanov; Emil Prodanov



Statistics:

Bioinformatics; probabilistic model selection; bootstrapping; Bayesian analysis; statistical network analysis; regression models with random effects; survival analysis & frailty; classification methods.

Researchers: John Butler; Joe Condon; Lida Fallah; Michael McAuley

Collaborators: Sustainability & Health



Mathematics Education:

Diagnostic testing; the transition to third-level education; the impact of the Project Maths curriculum on third-level education; problem-based learning in mathematics; online assessment.

Researchers: Cormac Breen; Blathnaid Sheridan

Collaborators: Dana Mackey; Milena Venkova; Mathematics Learning Centre (MLC)