About Georgios Leontidis
George is a Lecturer (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 techniqies 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 paper on Adapting Deep Neural Networks (CNN-RNN) for Detecting Parkinson's Disease in MRI scans, IEEE SSCI 2017 - http://eprints.lincoln.ac.uk/28713/1/ieeessci2017final_ready-preprint.pdf
PhD or MSc by Research: Looking for a self-funded students to work 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.
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)
Problem Solving - Level 1 - 2017-2018
Algorithms for Data Mining - Level 3 - 2017-2018
Business Processes - Level 2- 2016-2017 - Week B13
2 PhD Students
2 MSc by Research Students
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
Marie Curie Mirco-Grant
— MCAA-EU - 400£,
Marie Curie ITN 3-Year Research Fellowship
— EU-FP7 Marie Curie actions,
Prize for Best Undergraduate Thesis
-Member of the EPSRC Associate Peer Review College: Reviewing grants, prioritisation meetings, etc.
Currently reviewing for EPRSC IRC Next Steps Plus in Healthcare Technologies. 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