Staff Directory

About Georgios Leontidis

George is an Assistant Professor in Computer Science (Machine Learning). He is currently a Co-PI in the EU-H2020 project CORe Monitoring Techniques And EXperimental Validation And Demonstration (2017-2021), which aims to develop techniques for detecting faults in nuclear reactors, a Co-I in the EU-Interreg project SmartGreen (2017-2021), which will develop big data analytics and machine learning techniques for reducing energy consumption and costs in Greenhouses, and a Co-I in the EPSRC/Innovate UK project ARFMS (2017-2018), which targets to use deep learning/image processing techniques for automatically finding mistakes in the expiry dates in the labels of food packages. Previously he has worked as a Marie Curie Researcher in a project led by DVC Professor Andrew Hunter in the EU-FP7 Marie Curie actions REVAMMAD project. Before joining the academic staff at University of Lincoln, George worked for a leading company on radiation oncology in Germany as a Data Scientist and Program/Project Manager, working on defining quality assurance indexes for the whole treatment. This included predicting machine failures and treatment outcome, utilising machine learning, data analytics and big data processes. During this period, he actively collaborated with the University of Erlangen-Nuremberg in Germany and the University of California in San Francisco. His research outcomes have been published in various international journals, conferences and book chapters, and has also been invited to give interviews in a Radio station, newspapers and scientific magazines in regards to his novel research activity on early diagnosis of diabetic retinopathy. Georgios has also appeared in the annual magazine of the University of Lincoln. Our newly founded Machine Learning Research Group here in Lincoln is a member of the EPSRC Network on Computational Statistics and Machine Learning (NCSML). ----------------------------------------------------- Please check our latest papers on a) Adapting Deep Neural Networks (CNN-RNN) for Detecting Parkinson's Disease in MRI scans, IEEE SSCI 2017 - b) An adaptable deep learning system for optical character verification in retail food packaging, IEEE EAIS 2018 - c) A new unified framework for the early detection of the progression to diabetic retinopathy from fundus images - CBM, Elsevier - ----------------------------------------------------- %%%%%%%%%%%% PhD or MSc by Research: Looking for self-funded students to work in my Lab on various projects on deep learning and machine learning, across many applications e.g. Nuclear Plant & Gas Turbines failures, Parkinson’s disease, animal tracking and localisation, and retinal diseases. %%%%%%%%%%%%

Department Responsibilities

Deputy Programme Leader in CertHE/BSc/MComp in Computer Science Member of the School’s Progression Panel for Postgraduate Research Students Athena Swan Member Research, Teaching, Supervision of PGR students Office: INB3111 - Isaac Newton Building Office hours:  Wednesday 10.00-12.00 (otherwise email me first to arrange it) Teaching:  Problem Solving - Level 1 - 2017-2018 Algorithms for Data Mining - Level 3 - 2017-2018 Business Processes - Level 2- 2016-2017 - Week B13 Supervising: 2 Post-Doctoral Fellows 2 PhD Students 2 MSc by Research Students 1 Research Assistant

Subject Specialism

Deep Neural Networks, Data Science, Machine Learning, Data Mining, Statistical Modelling, Big Data, Image Processing, Medical Imaging, Medical informatics


  • PhD in Computer Science
  • MSc in Medical Informatics
  • BSc in Informatics Engineering


  • CORe Monitoring Techniques And EXperimental Validation And Demonstration - 155K - Co-I — EU-Horizon 2020,
  • Nvidia GPU Grant for Deep Learning — NVIDIA,
  • Marie Curie Mirco-Grant — MCAA-EU - 400£,
  • Marie Curie ITN 3-Year Research Fellowship — EU-FP7 Marie Curie actions,
  • Prize for Best Undergraduate Thesis — 2011


-Member of the EPSRC Full Peer Review College: Reviewing grants, prioritisation meetings, etc. -Editorial Board in Computers in Biology and Medicine, Elsevier -External Examiner at the University of Hull -Editor in the Directory of Open Access Journals managing a team of 6 Associate editors. -Reviewer in several journals, e.g. PLOS One, JMIR Biomedical Engineering, Computers in Biology and Medicine, Journal for Modeling in Ophthalmology, etc. -Invited keynote speaker in the 16th Annual conference of the British Association of Retinal Screening -Reviewer for NIPS 2018

Orcid ID


Research Interests

  • Data Science

  • Deep Learning

  • Machine Learning Applications

  • Statistical Modelling

  • Artifical Neural Networks

  • Big Data

Research Groups Memberships

Research Projects

  • CORe Monitoring Techniques And EXperimental Validation And Demonstration (Co-PI) - 4 years — awarded £155000 by EU-H2020 in 2017
  • Automated Robotic Food Manufacturing System (Optical Character Recognition) - (Co-I) - 1 year — awarded £139323 by EPSRC & IUK in 2017
  • SmartGreen - Interreg VB project BigData and eco-innovative resource use in the NSR Greenhouse industry (Co-I) — awarded £258114 by EU - ERDF in 2017
  • Gas Turbine Fault Detection — Siemens in 2017
  • Phase 2. The development of dynamic energy control mechanisms for food retailing refrigeration systems. — awarded £830099 by Innovate UK in 2016
  • REtinal Vascular Measurements, Modelling and Diagnosis (Researcher) — Marie Curie - EU in 2013

Research in the Lincoln Repository

Degree Responsibilities

  • Deputy Programme Leader - CertHE/BSc/MComp in Computer Science — 2017 to Present

Module Responsibilities

  • Lecturing - Problem Solving — 2017 to Present
  • Lecturing - Algorithms for Data Mining (Module Coordinator) — 2017 to Present
  • Lecturing - Business Processes — 2016 to 2017

Professional Affiliations

  • Higher Education Academy — Associate Fellow
  • Association for Research in Vision and Ophthalmology — Member
  • IEEE EMBS Society — Member
  • IEEE — Member
  • German Association for Medical Informatics, Biometry and Epidemiology — Member