Dr Archontis Giannakidis is currently a Senior Lecturer in Data Science with the School of Science and Technology. He is Module Leader for ''Discrete Mathematics & Computational Complexity'' (Year 2) and ''Convex Optimisation'' (Year 3), and supervises undergraduate final year and Masters dissertations. Dr Giannakidis’s research focuses on the intelligent processing of biomedical and other types of data. He advises PhD candidates in the above field.
Archontis is a Data Scientist specialising in Deep Learning. In 2010, he was awarded his PhD in Electronic Engineering (Subject Area: Inverse Problems) from the University of Surrey, Guildford, UK. He subsequently joined Berkeley National Laboratory, Berkeley, California, USA as a Postdoctoral Fellow Researcher for the Life Sciences Division. In 2013, he moved to Royal Brompton Hospital, London, UK to work as a Cardiac MR Image Analysis Scientist. In September 2017, Dr Giannakidis was appointed to the role of Senior Lecturer in Data Science for NTU. He was also affiliated with the National Heart and Lung Institute, Imperial College London, London, UK from 2013 to 2020.
Dr Giannakidis has participated in numerous cutting-edge research projects funded by UK (EPSRC, Innovate UK, BHF, GEO) and USA (NIH, Department of Energy).
His main research areas of interest are: Machine Learning, Deep Learning, Biomedical Image Analysis, Convolutional Networks, Sequence Models, Autoencoders, Probabilistic Graphical Models for Deep Learning, Deep Generative Models, Deep Reinforcement Learning, Diffusion MRI, Cardiovascular MRI.
His research focuses on the intelligent processing of large amounts of data towards: (i) automating intellectual tasks normally performed by humans, (ii) learning efficient (dense) data representations, (iii) revealing hidden patterns in the data, (iv) optimising decision-making.
Opportunities arise to carry out postgraduate research towards an MPhil / PhD in the areas identified above. Further information may be obtained on the NTU Research Degrees website https://www.ntu.ac.uk/research/research-degrees-at-ntu
Current PhD students:
- Tuan Aqeel Bohoran. Project title: Fully automated quantification of myocardial infarct size using artificial intelligence methods. Funding: European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 801604.
- David Gwillym Jenkins. Project title: Revolutionising landslide-tsunami prediction with advanced machine learning techniques. Funding: Internal.
Visiting PhD students:
- Michael Lystbaek (Department of Business Development and Technology, Aarhus University, Herning, Denmark). Project title: Developing an artificial intelligence application to support autonomous building design.
Dr Giannakidis has been a member of the International Society for Magnetic Resonance in Medicine (ISMRM), the Institute of Electrical & Electronic Engineers (IEEE), and the Technical Chamber of Greece. He is also a Fellow of the Higher Education Academy (FHEA).
Dr Giannakidis was in the organising committee for international conferences. He is a member of the Editorial Board of ‘‘Frontiers in Physiology’’, the 2nd most cited Physiology journal in the world. He is a regular reviewer for major international journals such as IEEE Transactions on Medical Imaging, Physics in Medicine and Biology, and Journal of Cardiovascular Magnetic Resonance. He has been asked to give numerous invited talks.
Sponsors and collaborators
- Project: Reform of the Gender Recognition Act 2004. Funding organisation: Government Equalities Office. Date of Award: 2018. PI: Prof Daniel King, Nottingham Business School, NTU. Total Funding: ~£50K. Role: Co-I (Deep Learning for automated coding of free-text responses).
- Project: Designing weight and cost optimised automotive joints for novel lightweight materials using computer-aided engineering. Funding organisation: Innovate UK / EPSRC Knowledge Transfer Partnership. Industrial Partner: FAR-UK. Date of Award: 2018. PI: Dr David Chappell, SST, NTU. Total Funding: ~£175K. Role: Co-I (Optimisation).
- Dr Grant T. Gullberg (Lawrence Berkeley National Laboratory, Berkeley, California, USA)
- Prof Gerry McCann (University of Leicester, Leicester, UK)
- Dr Valentin Heller (University of Nottingham, Nottingham, UK)
- Dr Polydoros Kampaktsis (Columbia University, New York, NY, USA)
- Dr Michail J. Beliatis (Aarhus University, Herning, Denmark)
Peer reviewed journal articles
- J14. Siouras A., Moustakidis S., Giannakidis A., Chalatsis G., Liampas I., Vlychou M., Hantes M., Tasoulis S., Tsaopoulos D. (2022). Knee injury detection using deep learning on MRI studies: A systematic review. Diagnostics 12(2):537.
- J13. Ghonim S., Ernst S., Keegan J., Giannakidis A., Spadotto V., Voges I., Smith G. C., Boutsikou M., Montanaro C., Wong T., Ho S. Y., McCarthy K. P., Shore D. F., Dimopoulos K., Uebing A., Swan L., Wei L., Pennell D. J., Gatzoulis M. A., Babu-Narayan S. V. (2020). 3D late gadolinium enhancement cardiovascular magnetic resonance predicts inducibility of ventricular tachycardia in adults with repaired tetralogy of Fallot. Circulation: Arrhythmia and Electrophysiology 13(11):8321.
- J12. Giannakidis A., Gullberg G. T. (2020). Transmural remodelling of cardiac microstructure of cardiac microstructure in aged spontaneously hypertensive rats by diffusion tensor MRI. Frontiers in Physiology 11:265.
- J11. Nielles-Vallespin S., Khalique Z., Ferreira P. F., de Silva R., Scott A. D., Kilner P., McGill L.-A., Giannakidis A., Gatehouse P. D., Ennis D., Aliotta E., Al-Khalil M., Kellman P., Mazilu D., Balaban R. S., Firmin D. N., Arai A. E., Pennell D. J. (2017). Evaluation of microstructural dynamics underlying myocardial wall thickening in-vivo by diffusion tensor cardiac magnetic resonance: validation and clinical translation in human dilated cardiomyopathy. Journal of the American College of Cardiology 69(6), 661--676.
- J10. Giannakidis A., Melkus G., Yang G., Gullberg G. T. (2016). On the averaging of cardiac diffusion tensor MRI data: The effect of distance function selection. Physics in Medicine and Biology 61(21):7765--7786.
- J9. Tran N., Giannakidis A., Gullberg G. T., Seo Y. (2016). Quantitative analysis of hypertrophic myocardium using diffusion tensor magnetic resonance imaging. Journal of Medical Imaging 3(4), 046001.
- J8. Giannakidis A., Gullberg G. T., Pennell D. J., Firmin D. N. (2016). Value of formalin fixation for the prolonged preservation of rodent myocardial microanatomical organization: Evidence by MR diffusion tensor imaging. The Anatomical Record 299(7), 878--887.
- J7. McGill L.-A., Ferreira P. F., Scott A. D., Nielles-Vallespin S., Giannakidis A., Kilner P. J., Gatehouse P. D., de Silva R., Firmin D. N., Pennell D. J. (2015). Relationship between cardiac diffusion tensor imaging parameters and anthropometrics in healthy volunteers. Journal of Cardiovascular Magnetic Resonance 18:2.
- J6. Giannakidis A., Nyktari E., Keegan J., Pierce I., Suman-Horduna I., Haldar S., Pennell D. J., Mohiaddin R., Wong T., Firmin D. N. (2015). Rapid automatic segmentation of abnormal tissue in late gadolinium enhancement cardiovascular magnetic resonance images for improved management of long-standing persistent atrial fibrillation. BioMedical Engineering OnLine 14:88.
- J5. McGill L.-A., Scott A. D., Ferreira P. F., Nielles-Vallespin S., Ismail T., Kilner P. J., Gatehouse P. D., de Silva R., Prasad S. K., Giannakidis A., Firmin D. N., Pennell D. J. (2015). Heterogeneity of fractional anisotropy and mean diffusivity measurements by in vivo diffusion tensor imaging in normal human hearts. PLoS ONE 10(7): e0132360. doi:10.1371/journal.pone.0132360.
- J4. Giannakidis A., and Petrou M. (2011). Improved 2-D vector field estimation using probabilistic weights. Journal of the Optical Society of America A 28(8), 1620--1635.
- J3. Petrou M., Giannakidis A. (2011). Full tomographic reconstruction of 2-D vector fields using discrete integral data. The Computer Journal 54(9), 1491--1504.
- J2. Giannakidis A., Petrou M. (2010). Sampling bounds for 2-D vector field tomography. Journal of Mathematical Imaging and Vision 37(2), 151--165.
- J1. Giannakidis A., Kotoulas L., Petrou M. (2010). Virtual sensors for 2D vector field tomography. Journal of the Optical Society of America A 27(6), 1331--1341.
- C2. Giannakidis A., Rohmer D., Veress A. I., Gullberg G. T. (2012). Diffusion tensor MRI-derived myocardial fiber disarray in hypertensive left ventricular hypertrophy: visualization, quantification and the effect on mechanical function. In Cardiac Mapping, 4th edition (M. Shenasa, G. Hindricks, M. Borggrefe, G. Breithardt, and M. E. Josephson. eds.). Wiley-Blackwell, Oxford, UK, pp. 574—588, ISBN: 9780470670460.
- C1. Giannakidis A., Petrou M. (2010). Conductivity imaging and generalized Radon transform: a review. In series Advances in Imaging and Electron Physics, Volume 162 (P. D. Hawkes, ed.). Academic Press, Burlington, Massachusetts, USA, pp. 129--172, ISBN: 9780123813169.
Peer reviewed conference proceedings
- P9. Bohoran, T. A., Kampaktsis P. N., McLaughlin L., Leb J., Moustakidis S., McCann G. P., Giannakidis A. (2023). Embracing uncertainty flexibility: Harnessing a supervised tree kernel to empower ensemble modelling for 2D echocardiography-based prediction of right ventricular volume. In the Proceedings of the 16th International Conference of Machine Vision (ICMV 2023), November 15-18, Yerevan, Armenia.
- P8. Lystbaek M., Giannakidis A., Beliatis M. J., Olsen M. (2023). Removing unwanted text from architectural images with multi-scale deformable attention-based machine learning. In Proceedings of the IEEE International Conference on Imaging Systems and Techniques (IEEE IST 2023). October 17-19, Copenhagen, Denmark.
- P7. Bohoran, T. A., Kampaktsis P. N., McLaughlin L., Leb J., Moustakidis S., McCann G. P., Giannakidis A. (2023). Right Ventricular Volume Prediction by Feature Tokenizer Transformer-Based Regression of 2D Echocardiography Small-Scale Tabular Data. In: Bernard, O., Clarysse, P., Duchateau, N., Ohayon, J., Viallon, M. (eds) Functional Imaging and Modeling of the Heart (FIMH 2023), June 19-22, Lyon, France. Lecture Notes in Computer Science, vol 13958. Springer, Cham, pp. 292--300.
- P6. Siouras A., Moustakidis S., Giannakidis A., Chalatsis G., Malizos K. N., Hantes M., Tasoulis S., Tsaopoulos D. (2022). Automated Recognition of Healthy Anterior Cruciate Ligament in Sagittal MR Images using Lightweight Deep Learning. In Proceedings of the 13th IEEE International Conference on Information, Intelligence, Systems and Applications (IEEE IISA 2022), July 18-20, Corfu, Greece.
- P5. Giannakidis A., Kamnitsas K., Spadotto V., Keegan J., Smith G., Glocker B., Rueckert D., Ernst S., Gatzoulis M. A., Pennell D. J., Babu-Narayan S., Firmin D. N. (2016). Fast Fully Automatic Segmentation of the Severely Abnormal Human Right Ventricle from Cardiovascular Magnetic Resonance Images using a Multi-scale 3D Convolutional Neural Network. In Proceedings of the 12th IEEE International Conference on Signal Image Technology & Internet Systems (IEEE SITIS 2016), November 28 - December 1, Naples, Italy, pp. 42--46.
- P4. Giannakidis A., Gullberg G. T. (2011). Tomographic Reconstruction of 3D Cardiac Diffusion Tensor Fields by Utilizing Reduced Number of Projection Measurements. In Proceedings of the 11th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully 3D 2011), July 11-15, Potsdam, Germany, pp. 455--458.
- P3. Neacsu F., Boutchko R., Giannakidis A., Gullberg G. T. (2010). A Level Set Approach to Segmenting a Deforming Myocardium from Dynamically Acquired SPECT Projection Data. In Conference Record of the 2010 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS MIC 2010), October 30 - November 6, Knoxville, Tennessee, USA, pp. 3588--3592.
- P2. Giannakidis A., Kotoulas L., Petrou M. (2008). Improved 2-D vector field reconstruction using virtual sensors and the Radon transform. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2008), August 20-24, Vancouver, British Columbia, Canada, pp. 2725--2728.
- P1. Petrou, M., and Giannakidis, A. (2008). Complete tomographic reconstruction of 2-D vector fields using a system of linear equations. In Proceedings of the 12th Annual Medical Image Understanding and Analysis Conference (MIUA 2008), July 2-3, Dundee, Scotland, UK, pp. 132--136.
Peer reviewed conference abstracts
- A15. Jenkins D. G., Heller V., Giannakidis A. (2022). Slide model-invariant prediction of landslide-tsunamis using machine learning. In the 7th IAHR Europe Congress, September 7-9, Athens, Greece.
- A14. Jenkins D. G., Heller V., Giannakidis A. (2021). Landslide-tsunami wave type classification using deep feed-forward neural networks. In the 2021 Young Coastal Scientists and Engineers Conference (YCSEC’ 21), March 29-30, National Oceanography Centre (virtual), Southampton, UK.
- A13. Ghonim S., Ernst S., Keegan J., Spadotto V., Giannakidis A., Voges I., Smith G. C., Lee S.-L., Boutsikou M., Montanaro C., Li W., Pennell D. J., Gatzoulis M. A., Babu-Narayan S. V. (2019). Late gadolinium enhancement CMR predicts ventricular tachycardia inducibility in repaired tetralogy of Fallot. In the 22nd Annual Scientific Sessions of the Society for Cardiac Magnetic Resonance (SCMR 2019), February 6-9, Bellevue, Washington, USA.
- A12. Giannakidis A., Oktay O., Keegan J., Spadotto V., Voges I., Smith G., Pierce I., Bai W., Rueckert D., Ernst S., Gatzoulis M. A., Pennell D. J., Babu-Narayan S., Firmin D. N. (2017). Super-resolution Reconstruction of Late Gadolinium Cardiovascular Magnetic Resonance Images using a Residual Convolutional Neural Network. In the 25th Scientific Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM 2017), April 22-27, Honolulu, HI, USA.
- A11. McGill L.-A., Ferreira P., Scott A. D., Nielles-Vallespin S., Giannakidis A., Kilner P. J., Gatehouse P. D., de Silva R., Firmin D. N., Pennell D. J. (2016). Diffusion Tensor Imaging: Comparison of Hypertrophic Cardiomyopathy, Hypertension and Healthy Cohorts. In the 14th European Association of Cardiovascular Imaging (EACVI) Annual Meeting on CMR (EUROCMR 2016), May 12-14, Florence, Italy.
- A10. Giannakidis A., Haldar S., Nyktari E., Keegan J., Suman-Horduna I., Pennell D . J., Wong T., Mohiaddin R., Firmin D. N. (2015). Rapid automatic segmentation of enhanced tissue in LGE MRI of long-standing persistent atrial fibrillation validated against endocardial voltage and lesion patterns. In the 23rd Scientific Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM 2015), May 30 - June 5, Toronto, Ontario, Canada.
- A9. Giannakidis A., Ferreira P., Gullberg G. T., Pennell D. J., Firmin D. (2015). Transmural gradients of preferential diffusion motility in the normal rat myocardium characterized by diffusion tensor imaging. In the SCMR-EuroCMR 2015 Joint Scientific Sessions, February 4-7, Nice, France.
- A8. Giannakidis A., Ferreira P., Scott A. D., Nielles-Vallespin S., Babu-Narayan S. V., Kilner P. J., Pennell D. J., Firmin D. (2014). Scanner-efficient diffusion tensor imaging of human cardiac microstructure using the fast composite splitting reconstruction algorithm. In the 17th Annual Scientific Sessions of the Society for Cardiac Magnetic Resonance (SCMR 2014), January 16-19, New Orleans, Louisiana, USA.
- A7. Giannakidis A., Melkus G., Liu J., Saloner D. A., Majumdar S., Gullberg, G. T. (2013). Fast-track cardiac diffusion tensor imaging with compressed sensing based on a novel circular Cartesian undersampling. In the 21th Scientific Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM 2013), April 20-26, Salt Lake City, Utah, USA.
- A6. Veress A. I., Giannakidis A., Gullberg, G. T. (2013). Mechanical effects of myofibril disarray on cardiac function. In the Proceedings of the American Society of Mechanical Engineering Summer Bioengineering Conference (ASME 2013), June 26-29, Sunriver, Oregon, USA.
- A5. Boutchko R., Fernandes A., Pan H., Abdalah M., Giannakidis A., Boswell M., Mitra D., Gullberg G. T. (2013). ReMI: An Object-relational Image Database for Nuclear Medicine Research. In the Proceedings of the 2013 Annual Meeting of Society for Nuclear Medicine (SNM 2013), June 8-12, Vancouver, British Columbia, Canada.
- A4. Giannakidis A., Veress A. I., Janabi M., O'Neil J. P., Abdullah O. M., Hsu E. W., Gullberg, G. T. (2012). Relating diffusion tensor MRI-derived alterations in myocardial microstructure to reduced wall motion in hypertensive left ventricular hypertrophy. In the 20th Scientific Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM 2012), May 5-11, Melbourne, Victoria, Australia.
- A3. Giannakidis A., Abdullah O. M., Brennan K. M., Hsu E. W., Gullberg, G. T. (2010). Assessment of Microstructure Variability in the Hypertrophied Myocardium using Diffusion Tensor MRI and the Log-Euclidean Computational Framework. In the 2010 World Molecular Imaging Congress (WMIC 2010), September 8-11, Kyoto, Japan.
- A2. Lutz T., Shi X., Giannakidis A., de Silva S., Goulianos A., Watts P. C. P., Yaici K., Evans B., Kondoz A., Petrou M., Silva, S. R. P. (2008). The Guardian Angel Project: Carbon nanotubes electrophysiological electrodes based unobtrusive wireless sensor network system to improve Health and Well-being in the 21st Century. In the 9th International Conference on the Science and Application of Nanotubes (NT '08), June 29 - July 4, Montpellier, France, pp. 310.
- A1. Hadjileontiadis L., Giannakidis A., Panas S. (2000). Alpha-stable modeling: a novel tool for classifying crackles and artifacts. In the 25th Annual International Conference on Lung Sounds (ILSA 2000), September 20-22, Chicago, Illinois, USA. MIUA 2008), July 2-3, Dundee, Scotland, UK, pp. 132