Antonios Nikitakis

Antonios Nikitakis is an engineer and a psychologist. He took his Engineer Diploma in Electrical and Computing Engineering from the Democritus University of Thrace, with specialization in Hardware Computer and Cryptography. He continued his studies in the Technical University of Crete where he received his Master Degree in Electronic and Computer Engineering in which he specialized in Computer Architecture and Hardware Design. In the same institution he fulfilled his Ph.D in Electronic and Computer Engineering with area of specialization the SoC Design in Computer Vision Applications. A part of his research which presented in his Thesis titled:  High Performance Low Power Embedded Vision Systems, rewarded in ESTIMedia 2012 with the Best paper award. At the same time, he graduated with a Bachelor Degree in Psychology from the Psychology Department of the University of Crete. He has years of experience as a Hardware Engineer working in the research and the industry. He has also collaborated with plenty of companies and university to carry out European Programs. Moreover, he has collaborated with experimental psychology labs and he combines his psychology knowledge with his expertise in computer vision and machine learning.

Konstantinos Makantasis

Konstantinos Makantasis received his computer engineering diploma from the Technical university of Crete (ECE, TUC, Greece) and his Master and PhD degrees from the school of Production Engineering and Management of the same University (DPEM, TUC, Greece). His diploma thesis entitled “Human face detection and tracking using AIBO robots”, while his master thesis entitled “Persons’ fall detection through visual cues”. In 2016 he successfully defended his PhD work focused on the detection and semantic analysis of object and events through visual cues. After his PhD, he was a employed as a Post-Doc Researcher at Dynamical Systems and Simulation Laboratory (DSSL-TUC, Greece), where he was mainly involved in the development of a trajectory planning module for autonomous vehicles through the utilisation of optimal control and dynamic programming methods. In 2017-2018, he was a Research Associate at KIOS Center of Excellence, University of Cyprus and working on the development of nonlinear tensor-based classifiers for high-order data analysis, and on the exploitation of reinforcement learning for optimal driving policies for autonomous vehicles. Currently, he is a Post-Doc researcher at the Institute of Digital Games, University of Malta working on affective computing problems. He is mostly involved and interested in computer vision, both for visual spectrum (RGB) and hyperspectral data, and in machine learning / pattern recognition and probabilistic programming. He has more than 40 publications in international journals and conferences on computer vision, signal and image processing and machine learning. He has been involved for more than 8 years as a researcher in numerous European and national competing research programs (Interreg, FP7, Marie Curie actions) towards the design, development and validation of state-of-the-art methodologies and cutting-edge technologies in data analytics and computer vision.

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Thanasis Papatahanasiou

Thanasis Papathanasiou acquired his engineering diploma in Information and Communication Systems Engineering from University of the Aegean (ICSD, Greece). His diploma thesis was “Implementation of a microcontroller-based system for monitoring and recording lean and acceleration” and he was a member of Robotics and Remote Sensing Research Team. He received his Master of Science diploma from Technical University of Crete (TUC, Greece) where he was a member of Optoelectonics and Imaging Diagnostics Research Group with his thesis titled “Colour Gamut Expansion with Spectral Imaging”. In parallel with his academic liabilities he was also employed as project manager and system engineer at QCell, a Startup Company located in Chania. Part of his responsibilities there was the development of a snapshot hyperspectral imager involving Colour reconstruction, Spectral Classification/Clustering and Spectral Estimation for utilizing the device in many application-specific fields. He has involved at design, implementation and testing for many imaging devices such as Visible and Hyperspectral Imagers for a variety of applications in commercial and scientific instrumentation markets. He has hands-on experimental experience on Optoelectronic setups and programming fluency in many languages and frameworks.