Projects per year
Organization profile
Profile Information
The Centre for Digital Innovation provides a multidisciplinary research and innovation environment in which our academics, researchers and students work collaboratively. We also work in collaboration with other Centres within and outside the University, across areas including health & wellbeing, biosciences, social science, engineering, business and education.
Our members work to meet the growing demand for digital technologies and media research and innovation in order to tackle the economic, societal and contemporary technological challenges we face today.
This requires the knowledge and understanding of how we can use technologies to enhance capacity and efficiency, increase productivity, improve accuracy and reduce costs to address real-world problems.
Our objectives are:
- To carry out research on state of the art digital technologies and media for health, business, engineering, social science and education domains
- To attract research, innovation and development funding in collaboration with local, national and international partners
- To further develop collaborative research and innovation on digital technologies and media with local and global partners
- To address societal, technological and economic challenges through the joint research effort of local and international experts
- To provide support or consultancy to global research, innovation and development activities linked with digital technologies, media and allied research
- To create industry and university collaborations in order to perform near to market research product development
- To create opportunities for placement based research in order to improve our students’ employability
- To create opportunities for young entrepreneurs to develop new markets through the global research platform
- To publish our research contributions in top quality journals and conferences
- To enhance digital technologies and media research in order to improve Quality of Life (QoL), Quality of Product (QoP) and Quality of Service (QoS)
Fingerprint
Network
Profiles
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Darren Abbott
- Centre for Digital Innovation
- Department of Computing & Games - Principal Lecturer (Enterprise & Business Engagement)
Person: Academic
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Paul Abley
- Centre for Digital Innovation
- Department of Computing & Games - Lecturer in Games Design
Person: Academic
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Usman Adeel
- Centre for Digital Innovation
- Department of Computing & Games - Senior Lecturer in Computer Science
Person: Academic
Projects
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Leverhulme Research Fellowship: "Incentives for Commitment Compliance"
12/12/20 → 5/12/22
Project: Research
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Thermodynamic models for carbon dioxide loaded amino acid solutions
1/12/20 → 30/11/22
Project: Research
Research output
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A Computational Model of Cancer Metabolism for Personalised Medicine
Occhipinti, A. & Angione, C., 6 Mar 2021, Building Bridges in Medical Science 2021. Cambridge Medical Journal, (Cambridge Medical Journal; vol. 28 Mar).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile -
A multimodal-Siamese Neural Network (mSNN) for person verification using signatures and EEG
Chakladar, D. D., Kumar, P., Roy, P. P., Dogra, D. P., Scheme, E. & Chang, V., 1 Jul 2021, In: Information Fusion. 71, p. 17-27 11 p.Research output: Contribution to journal › Article › peer-review
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A Script-based Approach for Teaching and Assessing Android Application Development
Modesti, P., 27 Jan 2021, In: ACM Transactions on Computing Education. 21, 1, 24 p., 7.Research output: Contribution to journal › Article › peer-review
Open AccessFile
Datasets
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of Multiplex methods provide effective integration of multi-omic data in genome-scale models
Angione, C. (Contributor), Conway, M. (Creator) & Liรณ, P. (Contributor), figshare, 1 Jan 2019
DOI: 10.6084/m9.figshare.10035350.v1, https://springernature.figshare.com/articles/of_Multiplex_methods_provide_effective_integration_of_multi-omic_data_in_genome-scale_models/10035350/1
Dataset
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of Multiplex methods provide effective integration of multi-omic data in genome-scale models
Angione, C. (Contributor), Conway, M. (Creator) & Liรณ, P. (Creator), figshare, 1 Jan 2019
DOI: 10.6084/m9.figshare.10035341.v1, https://springernature.figshare.com/articles/of_Multiplex_methods_provide_effective_integration_of_multi-omic_data_in_genome-scale_models/10035341/1
Dataset
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of Multiplex methods provide effective integration of multi-omic data in genome-scale models
Angione, C. (Contributor), Conway, M. (Creator) & Liรณ, P. (Creator), figshare, 1 Jan 2019
DOI: 10.6084/m9.figshare.10035353.v1, https://springernature.figshare.com/articles/of_Multiplex_methods_provide_effective_integration_of_multi-omic_data_in_genome-scale_models/10035353/1
Dataset
Press / Media
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Amnesty International UK - We Shall Fight Until We Win: Celebrating a century of pioneering political women
Fionnuala Doran
24/07/18
1 item of Media coverage
Press/Media: Press / Media
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Irish revolutionary in comic book form
Fionnuala Doran
8/08/16
1 item of Media coverage
Press/Media: Press / Media
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Review: The Trial of Roger Casement
Fionnuala Doran
1/10/16
1 Media contribution
Press/Media: Press / Media
Student theses
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Proof-theoretical observations of BI and BBI base-logic interactions, and development of phased sequence calculus to define logic combinations
Author: Arisaka, R., 12 Aug 2013Supervisor: Qin, S. (Supervisor)
Student thesis: Doctoral Thesis
File -
Computer aided analysis of paraspinal electromyography
Author: Coxon, A., 8 Feb 2013Supervisor: Longstaff, J. (Supervisor)
Student thesis: Doctoral Thesis
File -
Reasoning About C11 Programs with Fences and Relaxed Atomics
Author: He, M., 16 Feb 2018Supervisor: Qin, S. (Supervisor) & Ferreira, J. (Supervisor)
Student thesis: Doctoral Thesis