PACET 2017

4th Panhellenic Conference on Electronics and Telecommunications

Xanthi, 17-18 November 2017

Keynote Speakers

Short Bio
Alon Ascoli
Assistant Professor in the Faculty of Electrical and Computer Engineering
Technische Universität Dresden
Alon Ascoli received a Ph.D. Degree in Electronic Engineering from University College Dublin in 2006. From 2006 to 2009 he worked as RFIC analog engineer at CSR Sweden AB. From 2009 to 2012 he was Research Assistant in the Department of Electronics and Telecommunications at Politecnico di Torino. Since 2012 he is Assistant Professor in the Faculty of Electrical and Computer Engineering, Technische Universität Dresden. His research interests lie in the area of nonlinear circuits and systems, networks of oscillators, Cellular Nonlinear Networks and memristors. Dr. Ascoli was honored with the IJCTA 2007 Best Paper Award.

In April 2017 he was conferred the habilitation title as Associate Professor in Electrical Circuit Theory from the Italian Ministry of Education. Since 2014 he is Management Committee Substitute for Germany in the COST Action IC1401 MemoCIS "Memristors - Devices, Models, Circuits, Systems, and Applications". He has been Program Chair and Special Session Chair for the 15th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA) in 2016.

Mem-adaptive computing by memristor circuits
The future electronics will strongly rely on the use of neuromorphic circuits to compute data in a time- and energy-efficient fashion similarly as biological systems. Thereby, in order to overcome the limits of conventional von Neumann architectures, several recent investigations on novel signal processing paradigms adopt memristor neuron or synapse models, given their unique feature to combine memory and data computing capabilities in the same physical nano-scale volume. One interesting area where the use of memristors may find suitable application is in bio-inspired artificial neural networks known as Cellular Neural Networks (CNN). These are universal high-speed computing systems inherently based on the principle of “distributed computing with memory” and endowed with stored programmability on board. The dynamic behavior of these networks, first introduced by L.O. Chua in 1988, is exploited to accomplish multi-dimensional signal processing tasks (e.g. to solve pattern recognition/classification problems) or to model complex dynamics in biological systems (e.g. to capture pattern formation and wave propagation in locally-active reaction-diffusion systems). The principle of “combined sensing and computing” has been recently proposed also to control the motion of a limb of the humanoid robot Myon more quickly and under a lower energy expenditure than it is achieved under the state-of-the-art paradigm, without compromising on the adaptability to changes in the nominal operating conditions.