Dr Iraklis Giannakis

Dr Iraklis Giannakis
Lecturer
- About
-
School of Geosciences, University of Aberdeen
Meston Building, Kings College, Aberdeen, AB24 3FX
Biography
I received my bachelor and masters degree in geophysics from the Aristotle University of Thessaloniki in 2009 and 2011 respectively, where my research focused in near surface geophysics including electrical resistivity tomography (ERT), potential methods, seismics and ground penetrating radar (GPR).
In 2015 I received my PhD from The University of Edinburgh under a project co-funded by the Defence Science and Technology Laboratory (DSTL) and the Engineering and Physical Sciences Research Council (EPSRC). My research focused on numerical modelling of GPR for landmine detection and has been awarded with the best paper awart at the 15th International Conference of GPR. During my PhD, as a member of COST (European Cooperation in Science and Technology) Action TU1208, I was a visiting researcher at Roma Tre University working on applications of GPR to civil engineering. Subsequently, I was employed as postdoctoral researcher at Delft University of Technology (TUDelft) in the Microwave Sensing, Signals and Systems (MS3) group. There, I worked for D-Box, an industry oriented project aimed to deliver end-user tools for efficient demining. After finishing my national service in the Greek army I was employed by the University of Edinburgh under a project funded by Google fiber. Subsequently, I was employed by University of West London as a research fellow where I focused on applications of near surface geophysics and non-destructive testing for forestry and arboriculture applications. Lastly, I am a frequnet reviewer in journals associated with geophysics and I am part of the team behind gprMax, an open-source FDTD solver tuned for GPR.
My research focus and direction is on using innovative artificial intelligence concepts, signal processing and inversion to solve problems in applied geophysics and non-destructive testing. It is a novel combination of my background in geology/geophysics,and the experience I have developed in successfully employing machine learning and signal processing for non-destructive testing,and geophysical investigation. Consequently, my research extends across a wide range of disciplines and has focused on topics with high societal value such as landmine detection, marine geophysics and forestry applications. I have a robust theoretical and practical understanding of computational geophysics, inversion, signal processing, data science and neural networks and have collaborated with international researchers to apply these tools in electrodynamics, geophysics and non-destructive testing.
- Research
-
Research Overview
Data-driven interpretation and machine learning in exploration geophysics
Landmine detection using ground penetrating radar
Non-destructive testing for civil engineering and urban geophysics
Applications of near surface geophysics for forestry and arboriculture applications
- Publications
-
Page 1 of 5 Results 1 to 10 of 42
Extracting mud invasion information using borehole radar - A numerical study
Geophysics, vol. 88, no. 2, pp. D69-D83Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1190/geo2022-0121.1
- [ONLINE] View publication in Scopus
Deep learning–based nondestructive evaluation of reinforcement bars using ground-penetrating radar and electromagnetic induction data
Computer-Aided Civil and Infrastructure Engineering, vol. 37, no. 14, pp. 1834-1853Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1111/mice.12798
- [OPEN ACCESS] http://aura.abdn.ac.uk/bitstream/2164/19620/1/Li_etal_CCIE_deep_learning_based_AAM
- [ONLINE] View publication in Scopus
On the Limitations of Hyperbola Fitting for Estimating the Radius of Cylindrical Targets in Nondestructive Testing and Utility Detection
IEEE Geoscience and Remote Sensing Letters, vol. 19, 8029005Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/LGRS.2022.3195947
- [ONLINE] View publication in Scopus
The Use of GPR and Microwave Tomography for the Assessment of the Internal Structure of Hollow Trees
IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-14Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/TGRS.2021.3115408
- [OPEN ACCESS] http://aura.abdn.ac.uk/bitstream/2164/17654/1/Tosti_etal_IEEE_the_use_of_AAM
- [ONLINE] View publication in Scopus
A new era of planetary exploration: what we discovered on the far side of the moon
The ConversationContributions to Specialist Publications: ArticlesInferring the Shallow Layered Structure at the Chang’E-4 Landing Site: A Novel Interpretation Approach Using Lunar Penetrating Radar
Geophysical Research Letters, vol. 48, no. 16, e2021GL092866Contributions to Journals: ArticlesA Machine Learning Scheme for Estimating the Diameter of Reinforcing Bars Using Ground Penetrating Radar
IEEE Geoscience and Remote Sensing Letters (GRSL), vol. 18, no. 3, pp. 461-465Contributions to Journals: ArticlesOptimising the complex refractive index model for estimating the permittivity of heterogeneous concrete models
Remote Sensing, vol. 13, no. 4, 723Contributions to Journals: ArticlesFractal-Constrained Crosshole/Borehole-to-Surface Full Waveform Inversion for Hydrogeological Applications Using Ground-Penetrating Radar
Contributions to Conferences: Papers- [ONLINE] DOI: https://doi.org/10.1109/TGRS.2021.3054173
- [OPEN ACCESS] http://aura.abdn.ac.uk/bitstream/2164/16265/1/Manuscript.pdf
- [ONLINE] View publication in Scopus
A Deep Learning framework for Ground Penetrating Radar
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1109/IWAGPR50767.2021.9843168
- [ONLINE] View publication in Scopus