Lecturer
- About
-
- Email Address
- iraklis.giannakis@abdn.ac.uk
- Office Address
School of Geosciences, University of Aberdeen
Meston Building, Kings College, Aberdeen, AB24 3FX
- School/Department
- School of Geosciences
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
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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
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Page 4 of 6 Results 31 to 40 of 55
Health Monitoring of Tree-Trunks Using Ground Penetrating Radar
IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 10, pp. 8317-8326Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/TGRS.2019.2920224
The Use of Ground Penetrating Radar and Microwave Tomography for the Detection of Decay and Cavities in Tree Trunks
Remote Sensing, vol. 11, no. 18, 2073Contributions to Journals: ArticlesA Hybrid Optimization Scheme for Self-Potential Measurements Due to Multiple Sheet-Like Bodies in Arbitrary 2D Resistivity Distributions
Geophysical Prospecting, vol. 67, no. 7, pp. 1948-1964Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1111/1365-2478.12793
- [ONLINE] Deposit in University of Edinburgh repository
A Machine Learning Based Fast Forward Solver for Ground Penetrating Radar With Application to Full Waveform Inversion
IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 7, pp. 4417-4426Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/TGRS.2019.2891206
A CUDA-based GPU Engine for gprMax: Open source FDTD electromagnetic simulation software
Computer Physics Communications, vol. 237, pp. 208-218Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1016/j.cpc.2018.11.007
- [OPEN ACCESS] http://aura.abdn.ac.uk/bitstream/2164/14962/1/J6.pdf
- [ONLINE] View publication in Mendeley
Realistic FDTD GPR Antenna Models Optimized Using a Novel Linear/Nonlinear Full-Waveform Inversion
IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 3, pp. 1768-1778Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1109/TGRS.2018.2869027
Dagnosing Acute Oak Decline Using Ground Penetrating Radar
TerraEnvisionContributions to Conferences: Abstracts- [ONLINE] DOI: https://doi.org/10.3390/proceedings2019030024
- [OPEN ACCESS] http://aura.abdn.ac.uk/bitstream/2164/18634/1/A1.pdf
A Machine Learning Approach for Simulating Ground Penetrating Radar
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1109/ICGPR.2018.8441558
gprMax: Open Source Software to Simulate Electromagnetic Wave Propagation for Ground Penetrating Radar
Computer Physics Communications, vol. 209, pp. 163-170Contributions to Journals: ArticlesPredicting GPR performance for Buried Victim Search and Rescue
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings- [ONLINE] DOI: https://doi.org/10.1109/ICGPR.2016.7572642