Keynotes
A Reflection on Cybersecurity Indigenous Educational
Gautam Srivastava (Senior Member, IEEE) received the B.Sc. degree from Briar Cliff University, USA, in 2004, and the M.Sc. and Ph.D. degrees from t he University of Victoria, Victoria, BC, Canada, in 2006 and 2012, respectiv ely. Then, he taught for three years with the Department of Computer Scie nce, University of Victoria, where he was regarded as one of the top under graduate professors in computer science course instruction. From there in 2014, he joined a tenure-track position at Brandon University, Brandon, M B, Canada, where he is currently active in various professional and scholarl y activities. He was promoted to the rank of Professor in 2023. He, as he is popularly known, is active in research in the field of data mining and big data. In his ten-year acade mic career, he has published a total of 500 papers in high-impact conferences in many countries an d high-status journals (SCI and SCIE). He has delivered invited guest lectures on big data, cloud com puting, the Internet of Things, and cryptography at many international universities. He is an editor of several international scientific research journals. He currently has active research projects with other academics internationally.Â
Abstract
Decolonization and Indigenous education are at the forefront of Canadian content currently in Academia. Over the last few decades, we have seen some major changes in the way in which we share information. In particular, we have moved into an age of electronically-shared content, and there is an increasing expectation in Canada that this content is both culturally significant and relevant. In this paper, we explore the need for Cybersecurity education in rural Indigenous communities in Canada and the importance of community outreach initiatives. Throughout this project we Indigenized Cybersecurity course material, developed educational content and facilitated community engagement through workshops to assess the need for and knowledge of Cybersecurity. Our findings indicate that First Nation communities are very open to and have a strong desire to learn about Cybersecurity and online threats. The continued facilitation of workshops on First Nations reserves and development of educational material related to Cybersecurity is beneficial to Indigenous people and will aid in their pursuit of digital sovereignty as well as bridge the digital divide.Â
Gautam Srivastava
Department of Math and Computer Science,Brandon University, Brandon, Manitoba, Canada
Nicos Maglaveras
Professor of Medical Informatics Aristotle University of Thessaloniki Greece
Personalised health driven by digital health systems and multi-source health/environmental data, ML/AI/DL analytics and predictive models
Nicos Maglaveras received the diploma in electrical engineering from the Aristotle University of Thessaloniki (A.U.Th.), Greece, in 1982, and the M.Sc. and Ph.D. degrees in electrical engineering with an emphasis in biomedical engineering from Northwestern University, Evanston, IL, in 1985 and 1988, respectively. He is currently a Professor of Medical Informatics, A.U.Th. He served as head of the graduate program in medical informatics at A.U.Th, as Visiting Professor at Northwestern University Dept of EECS (2016-2019), and is a collaborating researcher with the Center of Research and Technology Hellas, and the National Hellenic Research Foundation.
His current research interests include biomedical engineering, biomedical informatics, ehealth, AAL, personalised health, biosignal analysis, medical imaging, and neurosciences. He has published more than 500 papers in peer-reviewed international journals, books and conference proceedings out of which over 160 as full peer review papers in indexed international journals. He has developed graduate and undergraduate courses in the areas of (bio)medical informatics, biomedical signal processing, personal health systems, physiology and biological systems simulation.
He has served as a Reviewer in CEC AIM, ICT and DGRT D-HEALTH technical reviews and as reviewer, associate editor and editorial board member in more than 20 international journals, and participated as Coordinator or Core Partner in over 45 national and EU and US funded competitive research projects attracting more than 16 MEUROs in funding. He has served as president of the EAMBES in 2008-2010. Dr. Maglaveras has been a member of the IEEE, AMIA, the Greek Technical Chamber, the New York Academy of Sciences, the CEN/TC251, Eta Kappa Nu and an EAMBES Fellow.
Abstract
The last years saw a steep increase in the number of wearable sensors and systems, mhealth and uhealth apps both in the clinical settings and in everyday life. Further large amounts of data both in the clinical settings (imaging, biochemical, medication, electronic health records, -omics), in the community (behavioral, social media, mental state, genetic tests, wearable driven bio-parameters and biosignals) as well as environmental stressors and data (air quality, water pollution etc.) have been produced, and made available to the scientific and medical community, powering the new AI/DL/ML based analytics for the identification of new digital biomarkers leading to new diagnostic pathways, updated clinical and treatment guidelines, and a better and more intuitive interaction medium between the citizen and the health care system.
Thus, the concept of connected and translational health has started evolving steadily, connecting pervasive health systems, using new predictive models, new approaches in biological systems modeling and simulation, as well as fusing data and information from different pipelines for more efficient diagnosis and disease management.
In this talk, we will present the current state-of-the-art in personalized health care by presenting cases from COVID-19 and COPD patients using advanced wearable vests and new technology sensors including lung sound and EIT, new outcome prediction models in COVID-19 ICU patients fusing X-Rays, lung sounds, and ICU parameters transformed via AI/ML/DL pipelines, new approaches fusing environmental stressors with -omics analytics for chronic disease management, and finally new ML/AI-driven methodologies for predicting mental health diseases including suicidality, anxiety, and depression.
