Andreas VOSS, Ernst-Abbe-Hochschule (EAH), Jena, Germany

Evidence of the effect of mindfulness training in college students through complex analysis of autonomic regulation

Andreas Voss was since 1997 Full Professor in Biosignal Processing and Medical Informatics at the Ernst-Abbe-Hochschule (EAH) in Jena, Germany. Before that, he worked as leader of the Biosignal Processing research group at the Max-Delbrueck-Centre for Molecular Medicine in Berlin. In 2015, he founded the Institute of Innovative Health Technologies IGHT at the EAH where he acts up to 2020 as the director and coordinated the research between five different departments. After his retirement, Professor Voss focuses on research in two main areas, autonomic regulation, and electronic senses (electronic nose). Here he works as a Guest Professor at two renowned German universities, the Institute of Biomedical Engineering and Informatics (BMTI) at the Technical University of Ilmenau and the Department of Pediatric Oncology and Hematology at Charité Berlin. He also led the medical evaluation in the Thuringian model of mindful universities.
His research interest are linear and non-linear analysis of multivariate and multiscale data and systems analysis (e.g., risk stratification in different diseases), characterizing autonomic regulation (heart diseases, schizophrenia, depression, stress...), time-frequency analyses, knowledge-based interpretation of physiological and pathophysiological regulations, and electronic senses (electronic nose). Prof. Voss (h-index 44, RG score 43.84) published more than 330 papers in peer reviewed journals. He is member of scientific societies (DGBMT, European Society of Cardiology, and IEEE), organizer, co-organizer, and associated editor of various national and international conferences as well as member of scientific boards of various other academic events and scientific journals. He acts as reviewer and for many international journals, conferences, and grant agencies.



Saeid SANEI, Nottingham Trent University, UK

Advances in EEG analysis for Detection of Interictal Epileptiform Discharges and their Roles in Deep Brain Stimulation for Seizure

Saeid Sanei received his PhD in Biomedical Signal and Image Processing from Imperial college London in 1991. Since then, he has been working in National University of Singapore, King’s College London, Cardiff University, University of Surrey, and currently in Nottingham Trent University (as a Professor of Signal Processing & Machine Learning) and Imperial College London (as an Academic Visitor). He is a Fellow of British Computer Society (FBCS) and a Senior Member of IEEE. Biosignal and Image Processing, Brain-Computer Interfacing (BCI), Assistive Technology, Bio-statistical Data Processing, Biomedical Systems Modelling, Body Sensor Networking, Speech, AI & Machine Learning, IoT for health monitoring are his main research areas. Prof Sanei published 5 books, a number of book chapters and edited books, and over 400 peer-reviewed publications. He has been an Associate Editor for the IEEE Signal Processing Magazine, IEEE Signal Processing Letters, and Journal of Computational Intelligence and Neuroscience. He organised and chaired a number of reputed conferences including the 44th IEEE International Conference in Acoustics, Speech, and Signal Processing (ICASSP 2019) in the UK.



José J. Rieta, Polytechnical University of Valencia, Spain

Artificial Intelligence for Groundbreaking Mobile Medicine in Cardiovascular Diseases

José J. Rieta received the M. Eng. degrees in Image and Sound Engineering from the Polytechnic University of Madrid, Spain, in 1991, the M. Sc. degree in Telecommunication Engineering and the Ph.D. degree in Biomedical Signal Processing from the Polytechnic University of Valencia (UPV), Spain, in 1996 and 2003, respectively. He is Full Professor at the Electronic Engineering Department of the UPV, becoming Lecturer since 1995. He has taught many subjects related to Electronic and Biomedical Instrumentation, Analog Systems, Data conversion Systems and Control Engineering, and has been the author of several academic publications in these areas.

As researcher he has coauthored about 90 publications in international Journals of his field, more than 300 international and national conference communications as well as 18 books or book chapters related to biomedical engineering and cardiovascular diseases.

Prof. Rieta has participated in more than 30 competitive research grants since the last 25 years, being the leader in 19 of them, with special mention to four National Research Grants from the Spanish Research State Plan. He has participated and leaded many agreements of technological transfer with companies related to biomedical engineering during last 20 years. As additional contributions to society, Dr. Rieta has performed an intensive training of young researchers with the supervision of 12 doctoral theses, where most of his trained researchers are now Lecturers and/or researchers at reputed universities, hospitals or expert engineers at private companies. In 2006 he founded the Biosignals & Minimally Invasive Technologies ( research group in the UPV, where is the CEO and responsible of the advanced biomedical signal processing line. His research interests include the application of artificial intelligence, statistical and non-linear signal processing to biomedical signals, specially focused in cardiovascular signals aimed at developing clinical solutions to study, monitor and characterize the cardiovascular system and cardiovascular pathologies.



Smaranda BELCIUG, University of Craiova, Romania

Artificial Intelligence in Healthcare. Applications in Oncology and Obstetrics/Gynecology

Smaranda Belciug is an Associate Professor at the Department of Computer Science, Faculty of Sciences, University of Craiova and Data Scientist at the Molecular Tumor Board – Multidisciplinary Commission for Personalized Therapeutic Indication based on a Comprehensive Molecular (Genetic) Assessment. She is a member of the Editorial Board at Springer Nature-BMC Medical Informatics and Decision Making, at the Journal of Medical Artificial Intelligence, and at the International Journals of Computers in Healthcare.

Her main research interests include Artificial Intelligence applied in the Healthcare system and Statistics. She is the author of the two monographs “Artificial Intelligence in Cancer: diagnostic to tailored treatment”, Elsevier, 2020, and “Intelligent Decision Support Systems – A journey to Smarter Healthcare”, Springer 2020. She is an enthusiastic partisan of the multidisciplinary approach in scientific studies, and all her research is driven by this reason. This has been recognized at multiple levels, from the wide variety of nature of the journals she has published into to the variety of journals and conferences that she reviews for.