Tutorial 1

Prof. Vangelis Metsis

Texas State University, USA

Title: Modern methods and tools for human biosignal analysis

Abstract: The term biosignal refers to any signal that can be measured from living organisms. Biosignals have been used in medicine, sports science, and psychology for diagnoses, and there have been impressive advancements in these areas. Recently, the fields of human-computer interaction and affective computing have found an interest in using biosignals as a means of understanding the human state and intention. This interest has been reinforced by the fact that acquiring information with sensors and interfacing electrically with the human body has become much easier in the past few years. Moving from large analog technologies to digital ones has led to the miniaturization of sensing devices. Wireless transmission technologies (e.g., Bluetooth low energy), which can be easily integrated with the acquisition hardware, have removed the need for bulky wiring. This tutorial will present an overview of modern applications of human biosignals and will provide practical examples of machine learning-based methods and tools for biosignal analysis. Traditional machine learning algorithms for feature extraction and classification will be compared with recent developments in deep learning and its applications to biosignal and time-series data processing in general. 


Dr. Metsis is an Assistant Professor at the Department of Computer Science at Texas State University. He joined the department in August 2014.

Dr. Metsis received his Bachelor of Science degree in Computer Science in 2005, from the Department of Informatics of Athens University of Economics and Business in Greece, and his Doctoral degree in 2011 from the Department of Computer Science and Engineering of The University of Texas at Arlington.

During 2006-2007, Dr. Metsis worked as a Research Associate at the Department of Informatics and Telecommunications of the National Center for Scientific Research (NCSR) “Demokritos” in Greece, contributing to the project MedIEQ, funded by the European Commission. After receiving his Ph.D. diploma, and until joining TxState, he was employed, as a Research Assistant Professor by UTA, and he continued to be affiliated with Heracleia Human-Centered Computing Laboratory, where he was involved in several federally-funded research projects, as a Co-PI or Senior Researcher. He also taught a number of graduate and undergraduate classes at the CSE department.

Dr. Metsis research interests span the areas of Machine Learning, Data Mining and Computer Vision with focus in applications of Smart Health and Wellbeing, Assisted Living and Bioinformatics.

Utilizing Field Programmable Gate Arrays (FPGA) for AI acceleration without noticing it !

Prof. Yannis Papaefstathiou  

Aristotle University of Thessaloniki, Greece

Three years ago, in AIAI I have presented an overview of how the designers can utilize FPGAs in their embedded systems, through the use of High-Level-Synthesis (HLS) Tools. In this tutorial we will dive into the new development approaches that allow the designer to take full advantage of FPGAs, both in the Cloud and on the Edge, while barely noticing that their core processing is executed on reconfigurable logic. The new emerging design flow is based on seamlessly utilizing open-source accelerated libraries that are being optimized for execution on the new highly heterogeneous FPGA-based systems.


Ioannis Papaefstathiou is an Associate Professor at the School of Electrical and Computer Engineering at Aristotle University of Thessaloniki and a co-founder of Exascale Performance Systems (EXAPSYS) which is a spin-off of Technical University of Crete and Foundation of Research and Technology Hellas (FORTH). From 2004-2018 he was a Professor at ECE School at Technical University of Crete and a Manager at Synelixis Solutions SA. He is working in the design and implementation methodologies for CPS with tightly coupled design parameters and highly constrained resources as well as in heterogeneous High Performance Computing (HPC) systems and the associated programming/development tools. He was granted a PhD in computer science at the University of Cambridge in 2001, an M.Sc. (Ranked 1st) from Harvard University in 1996 and a B.Sc. (Ranked 2nd) from the University of Crete in 1996.  He has published more than 100 papers in IEEE and ACM-sponsored journals and conferences. He has participated in numerous European R&D Programmes(e.g. OSMOSIS, FASTCUDA, HEAP, FASTER, COSSIM ECOSCALE, EXTRA); in total he has been Principal Investigator in 12 competitively funded research projects in Europe (in 7 of them he was the technical manager), in the last 7 years, where his cumulative budget share exceeds €5 million.