51cg

Professor Georgios Leontidis

Professor Georgios Leontidis
Professor Georgios Leontidis
Professor Georgios Leontidis

Professor, ELLIS Society Member

Personal Chair

51cg
Email Address
georgios.leontidis@abdn.ac.uk
School/Department
Provost





Biography

I am currently on sabbatical at UiT the Arctic University of Norway but I maintain my affiliation with UoA. I am a Chair in Machine Learning (at the point of promotion, aged 35, I was within the ~0.4% of the UK's youngest full professors) and a former member of the Scottish AI Alliance Leadership Member. I have a strong interest in both theoretical aspects of Machine/Deep Learning, e.g. capsule networks, domain adaptation, self-supervised learning etc., as well as applications, e.g. data imputation in environmental data of COSMOS-UK network (PI in NERC/EPSRC project ENTRAIN - NE/S016236/1, NE/S016244/1), homomorphic encryption with deep learning for enabling data sharing and analytics in food industry (PI - IoFT network plus EPSRC project), anomaly detection in nuclear reactors (Co-PI in H2020 project Cortex - 20 EU partners), Optimising retail refrigeration systems with machine learning (Co-PI-IUK project with Tesco), forecasting yield in strawberries and tomatoes (Co-PI-EU Interreg project SmartGreen and PhD studentship), Gas Turbine availability and fault prediction with Siemens Lincoln, etc. I am currently leading/co-leading several funded projects, including Enhancing Agri-Food Transparent Sustainability (PI), Predictive Emissions Monitoring System for Gas Turbines with Siemens Energy and Machine Learning and Expert-based System for Soft Fruit Yield Forecasting (Data Lab and Angus Soft Fruits).

Previously I was a Senior Lecturer at the University of Lincoln, a Senior Data Scientist at IBA Dosimetry in Germany and a Marie Curie ITN Fellow.

I serve as reviewer/AC in various top venues, such as NeurIPS/ICML/AAAI/ICLR, and participated in the UK AI Council’s Data Working Group ecosystem. I am also a member of the Full College of EPSRC and a panel college member of the UKRI FLF. I am also an External Examiner at Cranfield University (MSc applied AI).

 

Memberships and Affiliations

Internal Memberships
University Management Group (2022-March 2026)
University Research Committee (2024-March 2026)
Information Governance Committee (2023-March 2026)

Senate member (2020-2022)

Senate Business committee member (2020-2022)

External Memberships

BMVA 2025/2026 Summer School Chair

BMVC 2023 co-organiser and co-chair for ACs and Reviewers selection

Senior Expert Network, NERC Constructing a Digital Environment Programme ()

External Examiner of the MSc in Applied AI at Cranfield University (2020-2023)

External Examiner of the BSc in Computer Science, Hull University (2018-2022)

Sift and Interview panel member of the UKRI Future Leaders Fellowship scheme

Full College of EPSRC - member

AI Council’s Data Working Group ecosystem - member

Latest Publications

  • Enhancing Strawberry Yield Forecasting with Backcasted IoT Sensor Data and Machine Learning

    Ayall, T. A., Li, A., Beddows, M. A., Markovic, M., Leontidis, G.
    IEEE Transactions on AgriFood Electronics
    Contributions to Journals: Articles
  • Bottom-up emissions and energy assessment for decommissioning offshore platform structures in the North Sea: Brent and Tern case studies

    Jalili, S., Leontidis, G., Stone, M., Neilson, R.
    Environmental impact assessment review, vol. 119, 108398
    Contributions to Journals: Articles
  • VisionTreeS: A Hybrid Tree-Based Visual Masked Autoencoder Approach for Strawberry Yield Forecasting From Low-Resolution Data

    Beddows, M. A., Durrant, A., Leontidis, G.
    IEEE Transactions on AgriFood Electronics, vol. 4, no. 1, pp. 128-136
    Contributions to Journals: Articles
  • Personalised Multi-Task Federated Learning for Diabetic Retinopathy Medical Image Classification

    Li, Y., Sharma, P., Leontidis, G., Yi, D.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
  • Assessing the impact of nature-based solutions on soil health in sub-Saharan Africa through farmer-centred methods

    Bittner, D., Smith, J., Leontidis, G., Campbell, G. A., Biegel, J., Smith, P., Kuhnert, M., Skalský, R., Giuliani, L. M., Salik, A. W., Hallett, P., Burslem, D. F. R. P., Yakob, G., Mekuria, W., Phimister, E., Haileslassie, A., Tegegne, D., Norouzi, S., Chen, H., Gubry-Rangin, C., Khan, A.
    Environmental Research Letters, vol. 21, no. 4, 043004
    Contributions to Journals: Articles

View My Publications

Prizes and Awards

- TMLR - Action Editor

- ICLR 2025,2026 - Area Chair

- NeurIPS 2024,2025 - Area Chair

- Best Area Chair award, NLDL 2025

- Shortlisted, AUSA/UoA for "Outstanding Contribution to Accessibility and Inclusivity in Blended Learning (2021)"

- Ranked at Top 4% of the EPSRC Full Peer Review College

- NeurIPS 2020 & 2023, top 10% Reviewer out of ~7000

- EU commission FISA 2019 conference - best PhD paper award (PhD student:Aiden Durrant)

Research

Research Overview

I am interested in problems revolving around deep learning and machine learning, more specifically on domain adaptation, variational inference and self-supervised learning. I am also working on novel neural network architectures, such as Capsule Networks.

In terms of application areas, I have a strong interest in problems that ML can provide solutions primarily in environmental, industrial, food and healthcare settings.

My past and current activity involves working with national and international collaborators on nuclear reactor perturbation analysis, optimising retail refrigeration systems, gap filling in environmental time-series, domain adaptation for food retail packaging image quality detection, disease detection, and yield forecasting for strawberries and tomatoes

Research Specialisms

  • Artificial Intelligence
  • Neural Computing
  • Computer Vision
  • Machine Learning

Our research specialisms are based on the Higher Education Classification of Subjects (HECoS) which is , published under the licence.

Current Research

I am currently working on the following problems across several funded projects:

a) Agrifood sustainability with AI across several funded projects, such as the UKRI AI CDT SUSTAIN () and the EPSRC EATS project (

b) New routing algorithms for Capsule Networks in order to improve their run time and performance, whilst reducing the number of parameters

c) Yield forecasting for strawberries - we use mobile robots to collect data in a setting that our collaborators at the Univeristy of Lincoln have in the Riseholme campus. We collect time-series, image, depth and video data, so that we can develop new machine learning techniques that can accurately and robustly forecast yield in 1-, 2- and 3- weeks ahead

d) Predicting availability of gas turbines, a collaboration with Siemens Energy Industrial Turbomachinery Ltd.

Past Research

--Gap filling in environmental time-series, specifically for the Cosmos-UK network. We developed new data imputation techniques in order to fill the gaps in the time series using historical data from most of the Cosmos-UK sites across the UK () - project funded by NERC, EPSRC and Defra (NERC-led)

--Optimising demand side response of retail refrigeration systems with Machine Learning, a collaboration with Tesco and funded by Innovate UK

 

Collaborations

UK:

a) Centre for Ecology and Hydrology, Wallingford, with Matt Fry, Jon Evans, Steve Cole, Mike Bowes and John Wallbank

b) British Geological Survey, Keyworth, with Andy Kingdon and john Bloomfield

c) Sheffield University, Mike Mangan

d) University of Lincoln, MLearn group, LIAT and LCAS groups

e) Siemens Energy Industrial Turbomachinery Ltd.

International:

a) Chalmers University of Technology, Sweden with Christophe Demaziere and Paolo Vinai

b) Paul Scherrer Insitute, Switzerland with Hamid Dokhane

c) National Technical University of Athens, Greece with Andreas Stafylopatis and Georgios Alexandridis

d) Technical University of Madrid, Spain with Cristina Montalvo

e) Nuclear plant, UJV/Rez, Czech Republic, with Petr Stulik

Funding and Grants

    • Enhancing Agri-Food Transparent Sustainability (Uni of Aberdeen, with Universities of Nottingham and Dundee, and Scotland’s Rural College) – EPSRC£1.1M PI 01/2022 to 12/2024
    • UKRI AI Centre for Doctoral Training in Sustainable Understandable agri-food Systems Transformed by Artificial INtelligence (SUSTAIN) – UKRI/EPSRC£10.9M co-Director – 04/2024 to 09/2032, with Universities of Lincoln (lead), Queen’s Belfast and Strathclyde; >60 PhD studentships split equally across the four partners (£1.7M as local PI)
    • AI in the Biosciences Network (AIBIO-UK) – BBSRC£2MCo-I 09/2023 to 08/2028 led by the University of Nottingham, with Universities of Aberdeen, KCL, Manchester, Aberystwyth, Bristol, and Quadram Institute
    • A4IM: Affordable Low-field MRI Reference System – EURAMET-EU – £110K for Aberdeen (£3M in total) – Co-I – 09/2023 to 09/2026
    • More real than reality: using deep learning and generative models to resolve how people make sense of other people’s behaviour – SGSSS-ESRC PhD£70K – 10/2023 to 10/2027
    • Data for Net Zero (D4NZ) – Net Zero Technology Centre Ltd £1,06M – Co-I (work package leader on decision making) – 1/1/2022 to 01/05/2025
    • Machine Learning algorithms for microfluidic precision oncology assays – CENSIS – PI – £49,789 – 01/2023 to 01/2024
    • 20 Tenure-Track Interdisciplinary Fellows and 12 Interdisciplinary PhD studentships – Development Trust - £4M – Co-PI (jointly the five Interdisciplinary Directors, 51cg)
    • WYSA – NIHR consultancy on a protocol for AI application for mental health management – £50K (across 12 people) – 05/2022 to 05/2023
    • Machine Learning and Expert-based System for Soft Fruit Yield Forecasting – Data Lab Industrial Doctorate with Angus Soft Fruits £66K – 07/2021 to 07/2024
    • Opening the black box: helping AI to persuade without bias – SGSSS-ESRC PhD£70K – 10/2022 to 10/2026
    • Next Generation self-supervised Learning Systems for Vision Tasks – EPSRC HPC – PI44,640 GPU hours
    • iCASE EPSRC 4-year PhD studentship with Siemens Industrial Turbomachinery on Machine Learning for predictive emissions monitoring systems for gas turbine – PI - £118K (£89K EPSRC || £29K Siemens Energy)– 10/2021-10/2025
    • Data Trusts and Data Sharing in Food Supply Chains – EPSRC IoFT Network Plus £12K – PI – (£50K in total) – 09/2020-03/2021
    • NEXTGEN: Neural-network Encryption; eXploration of Techniques for secure aGricultural data processing – EPSRC IoFT Network Plus - £28K (£50K in total) PI – 03/2020 to 09/2020
    • Engineering Transformation for the Integration of Sensor Networks – NERC£114K PI – (£340K in total) – 02/2019 to 06/2020
    • Out of War Experiences: Hope for the Future (Metadata Analytics) – 165K£ (280K£ including match-funding) – EU H2020Co-I – University of Lincoln Coordinating – 2019 to 2022
    • BerryPredictor: Improving harvest forecasts, yield predictions and crop productivity by optimising zonal phytoclimates in covered strawberry production – Innovate UK – £80,000 Co-I – 09/2019 to 08/2022
    • CORe monitoring Techniques and Experimental validation and demonstration – EU H2020 £155K - Co-PI for Uni of Lincoln (~£5M in total) – 09/2017 to 08/2021 –
    • SmartGreen–Big Data and Eco-Innovative resource use in the NSR Greenhouse Industry – EU Interreg £530,000 (with 50% match funding) for UoL (~3M£ in total) – 09/2017 to 08/2021
    • The Development of Dynamic Energy Control Mechanisms for Food Retailing Refrigeration Systems – Innovate UK 845,510£ - Co-I for Uni of Lincoln (~3.5M in total) – 09/2016 to 11/2018 -
    • ReACT Refrigeration AI Control Technologies – BBSRC seeding catalyst £ 35K - Co-I – 10/2018 to 04/2019
    • Precision Agriculture: Machine Learning for Yield Prediction and Uncertainty Estimation - BBSRC-CTP-NPIF 4-year PhD studentship with NIAB - £99,300 - 10/2020 to 10/2024
Publications

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  • Enhancing Strawberry Yield Forecasting with Backcasted IoT Sensor Data and Machine Learning

    Ayall, T. A., Li, A., Beddows, M. A., Markovic, M., Leontidis, G.
    IEEE Transactions on AgriFood Electronics
    Contributions to Journals: Articles
  • Bottom-up emissions and energy assessment for decommissioning offshore platform structures in the North Sea: Brent and Tern case studies

    Jalili, S., Leontidis, G., Stone, M., Neilson, R.
    Environmental impact assessment review, vol. 119, 108398
    Contributions to Journals: Articles
  • VisionTreeS: A Hybrid Tree-Based Visual Masked Autoencoder Approach for Strawberry Yield Forecasting From Low-Resolution Data

    Beddows, M. A., Durrant, A., Leontidis, G.
    IEEE Transactions on AgriFood Electronics, vol. 4, no. 1, pp. 128-136
    Contributions to Journals: Articles
  • Personalised Multi-Task Federated Learning for Diabetic Retinopathy Medical Image Classification

    Li, Y., Sharma, P., Leontidis, G., Yi, D.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
  • Assessing the impact of nature-based solutions on soil health in sub-Saharan Africa through farmer-centred methods

    Bittner, D., Smith, J., Leontidis, G., Campbell, G. A., Biegel, J., Smith, P., Kuhnert, M., Skalský, R., Giuliani, L. M., Salik, A. W., Hallett, P., Burslem, D. F. R. P., Yakob, G., Mekuria, W., Phimister, E., Haileslassie, A., Tegegne, D., Norouzi, S., Chen, H., Gubry-Rangin, C., Khan, A.
    Environmental Research Letters, vol. 21, no. 4, 043004
    Contributions to Journals: Articles
  • Adaptive Quantum-Augmented Security Framework for Vehicle-to-Everything (AQAS-V2X) Communication

    Alqahtani, T., Sharma, P. K., Leontidis, G.
    Contributions to Conferences: Papers
  • Pushing the Limits of Sparsity: A Bag of Tricks for Extreme Pruning

    Li, A., Durrant, A., Markovic, M., Huang, T., Kundu, S., Chen, T., Yin, L., Leontidis, G.
    Transactions on Machine Learning Research, vol. 11/2025, 5122
    Contributions to Journals: Articles
  • Food Standards Agency Science Council Report of Project ‘Artificial Intelligence Applications in Food Safety and Authenticity’

    Pearson, S., Gregory, P., Nicholson, C., O'Brien, J. T., Borriello, P., Burton, E., Cummins, S., Healing, J., Oliver, T., Smith, R., Tildesley, M., Wastling, J., Leontidis, G.
    Commissioned by Science Council of the Food Standards Agency. Food Standards Agency. 64 pages
    Books and Reports: Commissioned Reports
  • EquiCaps: Predictor-Free Pose-Aware Pre-Trained Capsule Networks

    Konstantinou, A., Leontidis, G., Thota, M., Durrant, A.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
  • Capsule Network Projectors are Equivariant and Invariant Learners

    Everett, M., Durrant, A., Zhong, M., Leontidis, G.
    Transactions on Machine Learning Research, vol. 2025, no. 10, 4991
    Contributions to Journals: Articles
  • OmniNet: An Expandable Causal Inference Network for Multiple Modalities

    Zhou, Y., Leontidis, G., Zhong, M.
    Neural Computing and Applications, vol. 37, no. 19, pp. 13749–13763
    Contributions to Journals: Articles
  • Stereotypical Bias Amplification, and Reversal, in an Experimental Model of Human Interaction with Generative AI

    Allan, K., Azcona, J., Sripada, S., Leontidis, G., Sutherland, C., Phillips, L., Martin, D.
    Royal Society Open Science, 241472
    Contributions to Journals: Articles
  • Response to UKIPO Consultation on Copyright and Artificial Intelligence

    Zivkovic, P., Adebola, T., Allan, K., Ducato, R., Leontidis, G., Lombardi, C., Sinclair, A., Starkey, A., Sripada, S., Brown, A. (ed.), Jevremovic, N. (ed.)
    51cg: School of Law. 11 pages.
    Other Contributions: Other Contributions
  • Masked Capsule Autoencoders

    Everett, M., Zhong, M., Leontidis, G.
    Transactions on Machine Learning Research, pp. 1-15
    Contributions to Journals: Articles
  • Exploring Segment Anything Foundation Models for Out of Domain Crevasse Drone Image Segmentation

    Wallace, S., Durrant, A., Harcourt, W., Hann, R., Leontidis, G.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
  • Multimodal Federated Learning With Missing Modalities through Feature Imputation Network

    Poudel, P., Chhetri, A., Gyawali, P. K., Leontidis, G., Bhattarai, B.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
  • Embedding AI-Enabled Data Infrastructures for Sustainability in Agri-Food: Soft-Fruit and Brewery Use Case Perspectives

    Markovic, M., Li, A. H., Ayall, T. A., Watson, N. J., Bowler, A. L., Woods, M., Edwards, P., Ramsey, R., Beddows, M. A., Kuhnert, M., Leontidis, G.
    Sensors, vol. 24, no. 2024, 7327
    Contributions to Journals: Articles
  • Farm Explorer: A Tool for Calculating Transparent Greenhouse Gas Emissions

    Markovic, M., Germano, S., Garijo, D., Edwards, P., Li, A., Ayall, T. A., Ramsey, R., Leontidis, G.
    Contributions to Journals: Conference Articles
  • Accelerate Training of Personalised Multi-Task Federated Learning

    Li, Y., Sharma, P., Leontidis, G., Yi, D.
    Chapters in Books, Reports and Conference Proceedings: Conference Proceedings
  • LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations

    Alkhalefi, M. A. M. A. A., Leontidis, G., Zhong, M.
    Transactions on Machine Learning Research, pp. 1-16
    Contributions to Journals: Articles
  • The Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework: a proposed application of IDEAL principles to artificial intelligence applications in trauma and orthopaedics

    Farrow, L., Meek, D., Leontidis, G., Campbell, M., Harrison, E. M., Anderson, L.
    Bone & Joint Research, vol. 13, no. 9, pp. 507-512
    Contributions to Journals: Articles
  • Bottom-up formulations for the multi-criteria decision analysis of oil and gas pipeline decommissioning in the North Sea: Brent field case study

    Jalili Dargalusani, S., Leontidis, G., Cauvin, S., Gormley, K., Stone, M., Neilson, R.
    Journal of Environmental Management, vol. 365, 121491
    Contributions to Journals: Articles
  • Object-Centric Learning with Capsule Networks: A Survey

    De Sousa Ribeiro, F., Duarte, K., Everett, M. A., Leontidis, G., Shah, M.
    ACM Computing Surveys, vol. 56, no. 11, 291
    Contributions to Journals: Articles
  • Automatic segmentation of radar data from the Chang’E-4 mission using unsupervised machine learning: A data-driven interpretation approach

    Giannakis, I., Mcdonald, C., Feng, J., Zhou, F., Su, Y., Martin-Torres, J., Zorzano Mier, M., Warren, C., Giannopoulos, A., Leontidis, G.
    Icarus, vol. 417, 116108
    Contributions to Journals: Articles
  • A Multi-Farm Global-to-Local Expert-Informed Machine Learning System for Strawberry Yield Forecasting

    Beddows, M. A., Leontidis, G.
    Agriculture, vol. 14, no. 6, 883
    Contributions to Journals: Articles
  • Model pruning enables localized and efficient federated learning for yield forecasting and data sharing

    Li, A. H., Markovic, M., Edwards, P., Leontidis, G.
    Expert Systems with Applications, vol. 242, pp. 1-12
    Contributions to Journals: Articles
  • Specialist Advisory Group (SAG) on Applications of Artificial Intelligence to Environment Natural Resources & Agriculture Policy, Scottish Government - Workshop Report

    Brewer, M., Leontidis, G.
    Scottish Environment, Food and Agriculture Research Institutes (SEFARI). 4 pages
    Books and Reports: Commissioned Reports
  • Science in the age of AI: How artificial intelligence is changing the nature and method of scientific research

    The Royal Society, Leontidis, G.
    The Royal Society. 108 pages
    Books and Reports: Commissioned Reports
  • Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination methods

    Alkhalefi, M. A. M. A. A., Leontidis, G., Zhong, M.
    Transactions on Machine Learning Research, vol. 2024, no. 4, pp. 1-17
    Contributions to Journals: Articles
  • Automated Crevasse Mapping Using Deep Learning Foundation Models to Analyse Climate Change and Glaciology

    Wallace, S., Durrant, A., Harcourt, W. D., Leontidis, G.
    Contributions to Conferences: Oral Presentations
  • LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations

    Alkhalefi, M. A. M. A. A., Leontidis, G., Zhong, M.
    Working Papers: Preprint Papers
  • Segment Anything Model (SAM) for Automatic Crater Detection

    Giannakis, I., Bhardwaj, A., Sam, L., Leontidis, G.
    EGU General Assembly 2024, pp. 21146
    Contributions to Conferences: Abstracts
  • Masked Capsule Autoencoders

    Everett, M. A., Zhong, M., Leontidis, G.
    Working Papers: Preprint Papers
  • A flexible deep learning crater detection scheme using Segment Anything Model (SAM)

    Giannakis, I., Bhardwaj, A., Sam, L., Leontidis, G.
    Icarus, vol. 408, 115797
    Contributions to Journals: Articles
  • ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method

    Everett, M. A., Zhong, M., Leontidis, G.
    Transactions on Machine Learning Research, pp. 1-13
    Contributions to Journals: Articles
  • Preface

    Waiter, G., Lambrou, T., Leontidis, G., Oren, N., Morris, T., Gordon, S.
    Chapters in Books, Reports and Conference Proceedings: Forewords and Postscripts
  • LLEDA—Lifelong Self-Supervised Domain Adaptation

    Thota, M., Yi, D., Leontidis, G.
    Knowledge-Based Systems, vol. 279, 110959
    Contributions to Journals: Articles
  • Tabular Machine Learning Methods for Predicting Gas Turbine Emissions

    Potts, R., Hackney, R., Leontidis, G.
    Machine Learning and Knowledge Extraction, vol. 5, no. 3, pp. 1055-1075
    Contributions to Journals: Articles
  • S-JEA: Stacked Joint Embedding Architectures for Self-Supervised Visual Representation Learning

    Manova, A., Durrant, A., Leontidis, G.
    Working Papers: Preprint Papers
  • HMSN: Hyperbolic Self-Supervised Learning by Clustering with Ideal Prototypes

    Durrant, A., Leontidis, G.
    Working Papers: Preprint Papers
  • Decarbonising Our Food Systems: Contextualising Digitalisation For Net Zero

    Pearson, S., Brewer, S., Manning, L., Bidaut, L., Onoufriou, G., Durrant, A., Leontidis, G., Jabbour, C., Zisman, A., Parr, G., Frey, J. G., Maull, R.
    Frontiers in Sustainable Food Systems, vol. 7, pp. 1-8
    Contributions to Journals: Articles
  • Premonition Net, a multi-timeline transformer network architecture towards strawberry tabletop yield forecasting

    Onoufriou, G., Hanheide, M., Leontidis, G.
    Computers and Electronics in Agriculture, vol. 208, 107784
    Contributions to Journals: Articles
  • Model Pruning Enables Localized and Efficient Federated Learning for Yield Forecasting and Data Sharing

    Li, A., Markovic, M., Edwards, P., Leontidis, G.
    Working Papers: Preprint Papers
  • Attention-Based Deep Learning Methods for Predicting Gas Turbine Emissions

    Potts, R. L., Leontidis, G.
    Northern Lights Deep Learning Conference 2023 (Extended Abstracts)
    Contributions to Conferences: Posters
  • Deep learning techniques for in-core perturbation identification and localization of time-series nuclear plant measurements

    Papaoikonomou, A., Wingate, J., Verma, V., Durrant, A., Ioannou, G., Papagiannis, T., Yu, M., Alexandridis, G., Dokhane, A., Leontidis, G., Kollias, S., Stafylopatis, A.
    Annals of Nuclear Energy, vol. 178, 109373
    Contributions to Journals: Articles
  • EDLaaS: Fully Homomorphic Encryption Over Neural Network Graphs for Vision and Private Strawberry Yield Forecasting

    Onoufriou, G., Hanheide, M., Leontidis, G.
    Sensors, vol. 2022, no. 22, 8124
    Contributions to Journals: Articles
  • Hyperspherically Regularized Networks for Self-Supervision

    Durrant, A., Leontidis, G.
    Image and Vision Computing, vol. 124, 104494
    Contributions to Journals: Articles
  • Machine learning for analysis of real nuclear plant data in the frequency domain

    Kollias, S., Yu, M., Wingate, J., Durrant, A., Leontidis, G., Alexandridis, G., Stafylopatis, A., Mylonakis, A., Vinai, P., Demaziere, C.
    Annals of Nuclear Energy, vol. 177, 109293
    Contributions to Journals: Articles
  • AI-enabled Safe and Efficient Food Supply Chain

    Kollias, S., Ye, X., Yu, M., Duan, W., Leontidis, G., Swainson, M., Pearson, S.
    Research Excellence Framework (REF) 2021. 5 pages.
    Other Contributions: Other Contributions
  • Learning with Capsules: A Survey

    Ribeiro, F. D. S., Duarte, K., Everett, M. A., Leontidis, G., Shah, M.
    Working Papers: Preprint Papers
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