Prof. Massimo Marchiori
University of Padua, Italy
Speech Title: Smart Big Data for Business and Society
Abstract: In this keynotw we will explore some recent trends combining big data and data science together with smart data sources. We will introduce these combinations by showing practical examples that touch various settings, ranging from the public (people and local authorities) and also the private (companies and businesses). We will also show some key lessons learnt along the way, showing what are the main challenges in order to provide a successful solution, and last but not least to develop a successful commercial product.
Introduction to Prof. Massimo Marchiori:
Prof. Massimo Marchiori is an Italian mathematician and computer scientist. He is the professor in Computer Science at the University of Padua, and Research Scientist at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) in the World Wide Web Consortium. In July, 2004, he was awarded the TR35 prize by Technology Review (the best 35 researchers in the world under the age of 35). His current research interests include: Web and Internet (big data, social systems, knowledge management, information retrieval, search engines, AI). Cyber-Physical Systems (IoT, sensors, smart world), and the almighty field of Complex Systems, especially as far as Data Science and Network Science are concerned.
Prof. Victor Chang
Teesside University, UK
Speech Title: The Next Generation of AI-based Data Science and Analytics for Healthcare and Finance
Abstract: Data Science is an interdisciplinary area between computing, mathematics, statistics, analytics, methods, machine learning, data processing and domain expertise. Mastering Data Science often will need to have clear understanding about the data, which methods suitable to deal with the research challenges, extract important results and explain fully and accordingly to the goals of research or business requirements.
This keynote presents the latest research outputs for AI–based Data Science and Analytics services and methods that can analyze multiple disciplines including healthcare, finance, data center computing, social networks, security and weather studies. In particular, research outputs from two disciplines will be at the center of attention. First, the health informatics service allows us to understand more about tumor, genes and proteins, as well as interpret part of how our human body can function. This includes the study of malignant tumor and genes that are prone to certain types of cancers. The latest research on coronavirus analysis and predictive modeling can be explained.
Second, it is the financial deep learning, risk modeling and financial computation and algorithms. We can identify the correlation between the current and the past stock movement from the best matching scenarios. Various techniques and results will be discussed in details. These two real-life examples can represent one of the next generation of AI-based Data Science and Analytics Services.
Introduction to Prof. Victor Chang:
Victor Chang is a Full Professor of Data Science and Information Systems, School of Computing and Digital Technologies, Teesside University, Middlesbrough, UK, since September 2019. He was a Senior Associate Professor, Director of Ph.D. and MRes Programs at International Business School Suzhou (IBSS), Xi’an Jiaotong-Liverpool University (XJTLU), Suzhou, China. He joined XJTLU in June 2016. He is still a Visiting Researcher at the University of Southampton, UK. Previously he worked as a Senior Lecturer at Leeds Beckett University, UK, for 3.5 years. Within 4 years, he completed Ph.D. (CS, Southampton) and PGCert (Higher Education, Fellow, Greenwich) while working full time. Before becoming an academic, he has achieved 97% on average in 27 IT certifications. He won a European Award on Cloud Migration in 2011, IEEE Outstanding Service Award in 2015, best papers in 2012, 2015 and 2018, the 2016 European award: Best Project in Research, 2016-2018 SEID Excellent Scholar, Suzhou, China, Outstanding Young Scientist 2017, 2017 special award on Data Science, 2017-2019 INSTICC Service Awards and numerous awards since 2012. He is an Editor-in-Chief of IJOCI & OJBD journals, former Editor of FGCS, Editor of Information Fusion and Associate Editor of TII, and founding Conference Chair of IoTBDS http://www.iotbd.org, COMPLEXIS http://www.complexis.org, FEMIB http://femib.scitevents.org and IIoTBDSC http://iiotbdsc.com. He was involved in different projects worth more than £13 million in Europe and Asia. He has published 3 books as sole authors and the editor of 2 books on Cloud Computing and related technologies. He gave 18 keynotes at international conferences.
Dr. Peter Holowka
Werklund School of Education, Graduate Programs in Education, University of Calgary
Speech Title: Cloud Computing, Business Continuity, and Artificial Intelligence Education: A Retrospective on IT Infrastructure in Western Canadian K-12 during COVID-19
Abstract: At the height of the COVID-19 pandemic in 2020, educational leaders imposed social distancing measures around the world in order to protect vulnerable populations. This measure affected educational institutions globally, resulting in a shift to online learning for nearly all courses. Often, educational leaders decided that if a course could not be effectively taught online, that course would no longer be offered. A carpentry course is one example of a discontinued course as it required specialized equipment. Teaching students concepts in the field of Artificial Intelligence (AI) and Machine Learning (ML) similarly requires specialized computational equipment and software. However, due to earlier investments in cloud computing infrastructure, some educational institutions were able to continue offering computer science courses without interruption.
This presentation is on the educational infrastructure that makes it possible to teaching AI and ML, outside of a high-powered computer lab running specialized software --a traditional requirement. This has implications for business continuity planning, educational program sizes in computer science, capital spending, classroom design, and human resources planning.
This presentation builds on the findings of an exhaustive study of all 75 large K-12 districts in Canada's three westernmost provinces. Multiple case study analysis, followed by correlation analysis, was used to explore the nature of IT infrastructure and cloud computing use in these provinces. A data transformation model mixed methods triangulation design methodology was used. This study encompassed over 1.1 million students and a geographical area of 2,258,483 square kilometres.
Introduction to Dr. Peter Holowka:
Dr. Peter Holowka is passionate about digital transformation and technology leadership, particularly in education. His doctoral research was in cloud computing adoption and organizational leadership in K-12. His professional work and academic research aim to support teaching and learning by transforming the educational environment. He has received multiple awards for leadership and academic excellence. Beginning his career as a network and web design specialist, Dr. Holowka also advises a number of independent/private schools, businesses, and not-for-profit organizations. Outside of professional and academic pursuits, his passions include hockey, motorcycles, the performing arts, and travel.