Lecturer
- About
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- 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 6 of 6 Results 51 to 55 of 55
A Novel Piecewise Linear Recursive Convolution Approach for Dispersive Media Using the Finite-Difference Time-Domain Method
IEEE Transactions on Antennas and Propagation, vol. 62, no. 5, pp. 2669-2678Contributions to Journals: ArticlesA Method to Detect Displacements of Borehole Electrodes Through Electrical Resistivity Tomography
Contributions to Conferences: Papers- [ONLINE] DOI: https://doi.org/10.3997/2214-4609.20143376
Incorporating dispersive electrical properties in FDTD GPR models using a general Cole-Cole dispersion function
Contributions to Conferences: PapersModeling and Inversion of Self-Potential Anomalies Due to Sheet-Like Bodies Under the Presence of Arbitrary 2-D Resistivity Distribution
Contributions to Conferences: Papers- [ONLINE] DOI: https://doi.org/10.3997/2214-4609.20143364
Signal Processing for Tree-Trunk Investigation Using Ground Penetrating Radar
Contributions to Conferences: Papers- [ONLINE] DOI: https://doi.org/10.3997/2214-4609.201902601
- [OPEN ACCESS] http://aura.abdn.ac.uk/bitstream/2164/14047/1/C3.pdf