The emerging paradigm of self-structuring AI: theory and applications (Workshop)

Workshop  on Algorithms

Conducted by Prof. Damminda Alahakoon and Dr. Daswin De Silva 

Research Centre for Data Analytics and Cognition, La Trobe University, Australia

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Held at the Seminar Room, Computer Science and Engineering Dept., University of Moratuwa.

Abstract:

In this seminar, we will present the theory and applications of self-structuring artificial intelligence; an emerging paradigm of artificial intelligence, inspired by human cognition, which aims to address the challenges and complexities of decision-making in non-deterministic data-intensive environments. The theoretical underpinnings of self-structuring AI are composed of learning structures that autonomously evolve, spatially, temporally, laterally and semantically, in alignment with the dynamic, unlabelled, continuously generated nature of data in stochastic environments, process and entities. Incremental learning from evolving data and features, scalable information fusion from high-volume multimodal data, change detection from high-velocity data streams, sequence detection and prediction are some of the new algorithms within this paradigm that we have developed in our research centre. We will also present the application of these algorithms on real-life industry based projects, in smart cities, energy management, digital health, Internet of Things, and social media

 

Prof. Damminda Alahakoon; His key research expertise lies in the areas of Data Mining, Text Analytics, Artificial Intelligence, Cognitive Computing and Business Intelligence. His research laid the foundation for a technology start up called ‘Conscious Machines’ which is now operating from Melbourne. He works closely with the Australian Artificial Intelligence community and is a member of the Australian Artificial Intelligence Steering Committee.

Dr. Daswin De Silva; Daswin possesses a decade of experience in analytics as both an industry practitioner and an academic. Starting as a software engineer developing enterprise integration layers for business intelligence capabilities, he gradually shifted into the information management sphere with key focus on data warehousing technology. After a few years in the budding analytics industry, he joined the PhD program at Monash University focusing on Artificial Intelligence. Soon after the PhD, he pursued a post-doctoral research fellowship in the Platform Technologies Research Institute at RMIT University. He was also a postgraduate unit leader at Monash and was nominated for the Faculty Teaching Excellence Award. Prior to joining La Trobe, Daswin was at Deakin University. At Deakin, he developed two new units in data warehousing and business intelligence for the Master of Business Analytics. Besides his academic and professional expertise in analytics, Daswin is actively involved in industry engagement with both analytics software providers and service providers.