Learning Non-IIDness: The Good, the Bad and the Ugly

[AI3 & CFAR Distinguished Professor Lecture]
Learning Non-IIDness: The Good, the Bad and the Ugly (Hybrid event) by Professor Cao Longbing
16 Jan 2023 | 4.30pm (Singapore Time)

In real-world systems, organisations, their behaviours, data and outcomes are embedded with complicated interactions, coupling relationships, and heterogeneities, forming non-IIDness (Independent and Identically Distributed) which goes beyond the classic IID assumptions. This generally applies to any physical, social, economic, virtual, human-made, and hidden systems and organisations. Of the many system complexities, such non-IIDnesses are arguably more fundamental, complex and challenging to understand, quantify and compute, ranging from system constituents, subsystems, environments to the whole-of-system. 

In this talk, Prof Cao Longbing will briefly share his preliminary thoughts on the underlying problems and challenges in non-IIDness, limitations of the existing quantitative and computing paradigms, and some outlooks for foundational developments that go beyond existing general thinking, methodologies, and frameworks in statistics, artificial intelligence (AI), data science, and shallow to deep machine learning, etc.  

Prof Cao Longbing 
Australian Research Council (ARC) Future Fellow
University of Technology Sydney (UTS)
Founding Director
UTS Advanced Analytics Institute
Prof Cao Longbing is a Professor and an Australian Research Council Future Fellow (Professorial level) at the University of Technology Sydney (UTS). He is also the founding Director of UTS Advanced Analytics Institute (now Data Science Institute). Prof Cao was a recipient of an Australian Eureka prize and has served on different editorial roles, including the Editor-in-Chiefs of IEEE Intelligent Systems and Springer-Nature’s Journal of Data Science and Analytics. He has also created several data science initiatives including the IEEE International Conference on Data Science and Advanced Analytics. His broad research interest covers artificial intelligence (AI), data science, machine learning, behaviour informatics, complex intelligent systems, and their enterprise applications in public and private sectors.