Quan Bai is an associate professor at the School of Information & Communication Technology, University of Tasmania (UTAS), Australia. He is an active researcher in AI and leading the AI Research Group at UTAS. Quan’s research has been mainly focusing on multi-agent coordination, trust mining, knowledge management. He has over 120 research publications and involved in the organisation of a number of international conferences, including AAMAS, PRIMA, PRICAI and Australasian AI.

More details about Prof. Bai can be found at his official page.

Sankalp Khanna is a Principal Research Scientist and leads the Health Intelligence team at the CSIRO Australian e-Health Research Centre. His research is focussed on applying Artificial Intelligence and Machine Learning techniques to model, analyse, predict, simulate and optimise patient flow through Australian public hospitals, and develop explainable algorithms for delivering decision support that clinicians can interpret and trust. Solutions developed by Sankalp have helped reshape workflow and policy in hospitals in Australia and overseas. Sankalp is also Adjunct Associate Professor at the Queensland University of Technology and Griffith University, the Secretary of the Pacific Rim International Conference on Artificial Intelligence (PRICAI) Steering Committee, and a founding Fellow of the Australasian Institute of Digital Health.

More details about Dr. Khanna can be found at his official page.

More details about Prof. Nayak can be found at his official page.

Alok Sharma received the B.Tech. degree from the University of the South Pacific (USP), Suva, Fiji, in 2000 and the M.Eng. degree, and the Ph.D. degree in the area of pattern recognition from Griffith University, Brisbane, Australia, in 2001 and 2006, respectively. He was with the University of Tokyo, Japan (2010–2012), as a Research Fellow (under JSPS). He is a Senior Research Scientist at RIKEN Center for Integrative Medical Sciences, Japan. He also is an Adjunct Professor at the Institute for Integrated and Intelligent Systems (IIIS), Griffith University, Australia. He is also a visiting researcher at the University of Tokyo, Japan. He was a Professor at the USP, Fiji. He was a visiting lecturer at Tokyo Medical and Dental University (TMDU), Japan. He participated in various projects carried out in conjunction with Motorola (Sydney), Auslog Pty., Ltd. (Brisbane), CRC Micro Technology (Brisbane), the French Embassy (Suva), and JSPS (Japan). His research interests include artificial intelligence, computer security, human cancer classification, and proteomics. He has published over 150 scientific articles in these areas with h-index 44. He contributed in reviewing and editing several articles from journals and conferences. He is the recipient of Griffith award of academic excellence, Australia, 2002, and the Vice-Chancellor’s Prize for best research output, Fiji, 2013.

More details about Prof. Sharma can be found at his official page.

More details about Prof. Kang can be found at his official page.

Guandong Xu is a Full Professor in Data Science at the School of Computer Science and Data Analytics Institute, University of Technology Sydney, with PhD degree in Computer Science. His research interests cover Data Science, Recommender Systems, User Modelling, and Social Computing. He has published three monographs in Springer and CRC press, and 220+ journal and conference papers, including TOIS, TKDD, TKDE, TNNLS, TCYB, TMM, TSE, TSC, TIFS, VLDB, IJCAI, AAAI, SIGKDD, SIGIR, CVPR, NIPS, WWW, WSDM, ICDM, ICDE, ICSE, and FSE conferences. He is the Editor-in-Chief of Human-centric Intelligent Systems and the assistant Editor-in-Chief of World Wide Web Journal. He has been serving on the editorial board or as a guest editor for several international journals, such as TOIS, TII, TCSS, PR etc. He has received several Awards from the academic and industry community. He is elevated as the Fellow of the Institute of Engineering and Technology (IET) and Australian Computer Society (ACS) in 2022 and 2021, respectively.

More details about Prof. Xu can be found at his official page.

Xin Geng is a chair professor of Southeast University, China. His research interests include machine learning, pattern recognition, and computer vision. He has published over 100 refereed papers in these areas. He has been an Associate Editor of IEEE T-MM, FCS, Visual Intelligence and MFC, a Steering Committee Member of PRICAI, a Program Committee Chair for conferences such as PRICAI'18, VALSE'13, etc., an Area Chair for conferences such as IJCAI, CVPR, ACMMM, ICPR, and a Senior Program Committee Member for conferences such as IJCAI, AAAI, ECAI, etc. He is a Distinguished Fellow of IETI and a Senior Member of IEEE.

More details about Prof. Cao can be found at his official page.

Zhi-Hua Zhou is a Professor of Computer Science and Artificial Intelligence at Nanjing University, China. He has made significant contributions to ensemble learning, multi-label learning, and weakly supervised learning. He is a Fellow of the AAAI, ACM, AAAS, IEEE, IAPR, and recipient of the IEEE Computer Society Edward J. McCluskey Technical Achievement Award, PAKDD Distinguished Contribution Award, ACML Distinguished Contribution Award. He served/s as Program Chair for IJCAI-19, AAAI-21, General Chair for PRICAI-18, ICDM-16, Series Editor of Lecture Notes in Artificial Intelligence, and Advisory Board of member AI Magazine.

More details about Prof. Zhou can be found at his official page.

R.G. (Randy) Goebel is currently professor of Computing Science in the Department of Computing Science, adjunct Professor in the Department of Medicine in the Faculty of Medicine and Dentistry, at the University of Alberta. He is also Fellow and co-founder of the Alberta Machine Intelligence Institute (Amii). He received the B.Sc. (Computer Science), M.Sc. (Computing Science), and Ph.D. (Computer Science) from the Universities of Regina, Alberta, and British Columbia, respectively.

Professor Goebel's theoretical work on abduction, hypothetical reasoning and belief revision is internationally well known; his recent research is focused on the formalization of visualization and explainable artificial intelligence (XAI), especially in applications in autonomous driving, legal reasoning, and precision health. He has worked on optimization, algorithm complexity, systems biology, natural language processing, and automated reasoning.

Randy has previously held faculty appointments at the University of Waterloo, University of Tokyo, Multimedia University (Kuala Lumpur), Hokkaido University (Sapporo), visiting researcher engagements at National Institute of Informatics (Tokyo), DFKI (Germany), and NICTA (Australia); he is actively involved in collaborative research projects in Canada, Japan, Germany, France, the UK, and China.

More details about Prof. Goebel can be found at his official page.

Professor Geoff Webb is an eminent and highly-cited data scientist. He was editor in chief of the Data Mining and Knowledge Discovery journal, from 2005 to 2014. He has been Program Committee Chair of both ACM SIGKDD and IEEE ICDM, as well as General Chair of ICDM and member of the ACM SIGKDD Executive. He is a Technical Advisor to machine learning as a service startup BigML Inc and to recommender systems startup FROOMLE. He developed many of the key mechanisms of support-confidence association discovery in the 1980s. His OPUS search algorithm remains the state-of-the-art in rule search. He pioneered multiple research areas as diverse as black-box user modelling, interactive data analytics and statistically-sound pattern discovery. He has developed many useful machine learning algorithms that are widely deployed. His many awards include IEEE Fellow, the inaugural Eureka Prize for Excellence in Data Science (2017) and the PAKDD Distinguished Research Contributions Award (2022).

More details about Prof. Webb can be found at his official page.

More details about Prof. Ho can be found at his personal page.

More details about Prof. Zhang can be found at his official page.

Hiroshi Motoda is Professor Emeritus of Osaka University and is now retired. He was a scientific advisor at AFOSR/AOARD (Asian Office of Aerospace Research and Development, Air Force Office of Scientific Research, US Air Force Research Laboratory) since 2006 till 2018, and worked as an international program officer. Before that, he was a professor at ISIR (Institute of Scientific and Industrial Research) of Osaka University since 1996 until 2006. Further before joining the university, he had been with Hitachi, Ltd. since 1967, participated in research on nuclear reactor core management, control and design of nuclear power reactors, expert systems for nuclear power plant diagnosis at the Central Research Laboratory (1967-1971), the Atomic Energy Research laboratory (1971-1978) and the Energy Research Laboratory (1978-1985), and on artificial intelligence, machine learning, knowledge acquisition, qualitative reasoning and diagrammatic reasoning at the Advanced Research Laboratory (1985-1995). He continued to work on machine learning and knowledge acquisition, and has extended his research to scientific knowledge discovery and data mining at Osaka University. At AOARD he had worked on social network analysis while funding basic research in Asian Countries and managing several tens of projects in computational intelligence. He was the principal investigator of the active mining project funded by MEXT (the Japanese Ministry of Education, Culture, Sports, Science and Technology) that involved about 20 universities and research institutes (2001-2004). He received his Bs, Ms and PhD degrees, all in nuclear engineering from the University of Tokyo. He was on the board of trustee of JSSST (the Japan Society of Software Science and Technology), JSAI (the Japanese Society for Artificial Intelligence) and JCSS (the Japanese Cognitive Science Society), and on the scientific advisory board of Alberta Ingenuity Center of Machine Learning. He was the chair of SIG-KBS and SIG-FAI of JSAI, the chair of the SC (steering committee) of PAKDD (Pacific Asian Conference of Knowledge Discovery and Data Mining), DS (International Conference on Discovery Science), ACML (Asian Conference on Machine Learning), and on the editorial board of JSAI, JCSS and Knowledge Acquisition (Academic Press), IEEE Expert, Knowledge and Information Systems: An International Journal (Springer), Advanced Engineering Informatics (Elsevier), International Journal of Human-Computer Studies (Elsevier), Intelligent Data Analysis: An International Journal (IOS Press) and International Journal of Data Science and Analytics (Springer). He is now an honorary member of the SC of PRICAI, ACML and DS, a life long member of the SC of PAKDD, and a member of the SC of DSAA (IEEE International Conference on Data Science and Advanced Analytics). He received the best paper awards twice from Atomic Energy Society of Japan (1977, 1984), four times from JSAI (1989, 1992, 2000, 2018), the best research paper award for DSAA2014 (2014), the outstanding achievement awards from JSAI (2000), the distinguished contribution award for PAKDD (2006), PRICAI (2014) and ACML (2018), the outstanding contribution award from Web Intelligence Consortium (2008), He co-authored/co-edited four books on feature selection/extraction/construction. His book ``Fundamentals of Data Mining'' was awarded the 2007 Okawa Publishing Prize. He was a member of AESJ, ANS, AAAI, IEEE, JCSS, IPSJ and is a member of JSAI (Fellow).

More details about Prof. Motoda can be found at his personal page.

More details about Prof. Walsh can be found at his official page.