Prof. Yanguo Jing
Associate Dean of Faculty of Business and Law
Coventry University, UK
Title: Artificial intelligence applications in sports performance
Abstract: Artificial Intelligence (AI) are being used in many aspects of business and society to create new values and opportunities. There are many challenges in developing these AI applications. In this talk, Yanguo will share his own journey of use artificial intelligence and machine learning to moninor sports performance, and evaluating their effectiveness in assessing energy expenditure during sport exercise.
Bio: Professor Dr Yanguo Jing is the Associate Dean (Enterprise and Innovation) at the Faculty of Business and Law, Coventry University, UK. He is a Professor in Enterprise and Innovation in Leadership and Artificial Intelligence. He has a PhD (Heriot-Watt University, UK), a MSc and a 1st class BSc (Hons) in Computer Science. He has over 20 years’ teaching, research and commercial experience in China, UK and the US. Yanguo is a Certified Management & Business Educator, a Fellow of the British Computer Society, a Charter IT professional and a Fellow of the Higher Education Academy in the UK. Yanguo has been instrumental in bringing in large executive education contracts from the public sector and Civil Servant including the Civil Servant Future Leaders Scheme, a DIT leadership programme in UK High Commission in India, Chevening Ethiopia Fellowship, Level 7 Senior Leader MBA apprenticeship contract from Ministry of Justice, and the Financial Fraud e-learning project with the City of London Police.
Assoc. Prof. Chinthaka Premachandra
Manager of Image Processing and Robotics Lab
Shibaura Institute of Technology, Japan
Bio: Chinthaka Premachandra (Member, IEEE) was born in Sri Lanka. He received the B.Sc. and M.Sc. degrees from Mie University, Tsu, Japan, in 2006 and 2008, respectively, and the Ph.D. degree from Nagoya University, Nagoya, Japan, in 2011.
From 2012 to 2015, he was an Assistant Professor with the Department of Electrical Engineering, Faculty of Engineering, Tokyo University of Science, Tokyo, Japan. From 2016 to 2017, he was an Assistant Professor with the Department of Electronic Engineering, School of Engineering, Shibaura Institute of Technology, Tokyo. In 2018, he was promoted to an Associate Professor with the Department of Electronic Engineering, School of Engineering/Graduate School of Engineering and Science, Shibaura Institute of Technology, where he is currently the Manager of the Image Processing and Robotic Laboratory. His laboratory conducts research in two main fields: image processing and robotics. The former field includes AI, computer vision, pattern recognition, image processing, and camera-based intelligent transportation systems, while the latter field includes mobile robotics, aerial robotics, and integration of terrestrial robot and aerial robot.
Assoc. Prof. Thippa Reddy Gadekallu
School of Information Technology and Engineering
Vellore Institute of Technology, India
Title: Federated Learning for Healthcare
Abstract: Health care is predominantly regarded as a crucial consideration in promoting the general physical and mental health and well-being of people around the world. The amount of data generated by healthcare systems is enormous, making it challenging to manage. Many machine learning approaches were implemented to develop dependable and robust solutions to handle the data. Machine learning (ML) cannot fully utilise data due to privacy concerns. This primarily happens in the case of medical data. Due to a lack of precise clinical data, machine learning (ML) does not appear to be a fitting solution for data related problems. Federated learning (FL) appears to be a promising solution to this problem. In this presentation, the applications of FL for healthcare informatics are discussed. Later, a discussion on the need for FL in healthcare domain is initiated. Then, the fundamentals of FL, and the major motivations behind FL for healthcare applications are presented. Then the applications of FL along with recent state-of-the-art in several verticals of healthcare are presented. Then lessons learnt, open issues and challenges that are yet to be solved are also highlighted. This is followed by future directions that give directions to the prospective researchers willing to do their research in this domain.
Bio: Dr. Thippa Reddy Gadekallu is currently working as Associate Professor in School of Information Technology and Engineering, VIT, Vellore, Tamil Nadu, India. He obtained his B.Tech. in CSE from Nagarjuna University, India, M.Tech. in CSE from Anna University, Chennai, Tamil Nadu, India and completed his Ph.D in VIT, Vellore, Tamil Nadu, India. He has more than 14 years of experience in teaching. He has than 100 international/national publications in reputed journals and conferences. Currently, his areas of research include Machine Learning, Internet of Things, Deep Neural Networks, Blockchain, Computer Vision. He is an editor in several publishers like Springer, Hindawi, Plosone, Scientific Reports (Nature), WIley. He also acted as a guest editor in several reputed publishers like IEEE, Springer, Hindawi, MDPI. He is recently recognized as one among the top 2% scientists in the world as per the survey conducted by Elsevier in the year 2021.