Keynote Speaker
Professor, Australian Institute of Health Innovation, Center for Health Informatics, Macquarie University, Sydney, Australia
Title: Health Informatics in the Age of AI
Bio: Dr. Berkovsky leads the Precision Health stream at the Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University. He focuses on the use of Artificial Intelligence methods to develop patient models and personalised predictions of diagnosis and care. He also studies how sensors and physiological responses can predict medical conditions, and how clinicians and patients interact with health technologies. Computer Scientist by training, he has theoretical and applied expertise in several areas related to human-centric applications of Artificial Intelligence and Machine Learning. His core research areas are user modelling, personalisation, and recommender systems, which lie on the intersection of Data Science and Human-Computer Interaction. As such, his work is around the interaction of people with information, technologies, and other people. Other areas of experise include behaviour change technologies, exergaming, and human aspects of cybersecurity.
Abstract: This talk will overview the breadth of research carried out by the Centre for Health Informatics at the Australian Institute of Health Innovation. We will initially discuss the 3 streams of ongoing work – Precision Health, Human-Technology Interaction, and Physiological Clinical Predictors – and then delve into the upcoming promising directions inspired by the recent developments in sensing technologies and AI.
Assistant Professor working with the school of Computer Science and Technology, Shandong University, China
Title: Spatial Data Management for Medicine and Healthcare
Bio: Dr. Dejun Teng is an Assistant Professor working with the school of Computer Science and Technology, Shandong University. He received his Ph.D. in Computer Science from the State University of New York, Stony Brook, M.S. in Computer Science from Emory University and B.E. in Software Engineering from Xi'an Jiaotong University, China, respectively. Dr. Teng’s research interests lie in Big Data, Computer Systems, Spatial Data Management, and Geographic Information Systems (GIS). He has published more than 10 papers in premier journals and conferences including VLDB, ICDE, ICDCS, SIGSPATIAL, and TOS. He is a member of the IEEE and the ACM.
Abstract: The development of spatially enabled applications such as the Internet of Things and ubiquitous positioning services leads to strong demands for efficient spatial data processing in both 2D and 3D space. Meanwhile, large-scale spatial data has gained extensive attention in the medicine and healthcare domain with the development of contact tracing, medical imaging, human atlases, and digital pathology. While significant effort has been made on studying distributed spatial data processing, there exist major challenges to the efficient processing of complex spatial objects, such as complex polygons with many edges, and 3D polyhedrons with many faces, with traditional spatial models and Filter and Refine Strategy. For instance, pathologists want to conduct queries over spatial data extracted from 2D or 3D medical images for better diagnosing the development of diseases. In the contact tracing scenario, it is critical to retrieve the contacted individuals from billions of trajectories in real-time. In this talk, I will introduce typical researches we have conducted for improving the efficiency of managing the spatial data in medicine and healthcare domains.