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Keynote Speaker
Keynote Speaker
Prof. Ethan Hadar, Tel-Hai University
Prof. Ethan Hadar is the Founding Dean of the School of Engineering at Tel-Hai University and has over thirty years of experience in the tech industry and academia, holding leadership roles such as Managing Director, CTO, SVP, and Distinguished Engineer at global organizations like Accenture, CA Technologies, and IBM. In addition to his role as a Dean, he is the Managing Director of Europe Market Wide Center of Excellence for Advanced AI at Accenture. His work focuses on integrating academic theory with practical AI applications to drive innovation across various sectors such as defense, cybersecurity, industry, and healthcare.
Prof. Hadar has 100 granted patents and patent applications, out of a total of 179 publications in areas including Generative AI, Digital Twins, Data Sciences, Software Architecture, Security, and Computer Vision. Prof. Hadar is a Professor-of-Practice for Information Systems and Software Engineering, holding a PhD in Operations Research and System Analysis, and an M.Sc. in Mechatronics from the Technion, Israel Institute of Technology. His notable innovations include Generative AI for cybersecurity, semantic sensor data fusion, smart data mesh integration, knowledge graphs design tools, and a Digital Twins platform. Prof. Hadar's dual roles have allowed him to bridge the gap between theoretical knowledge and practical application, leading to impactful research and industry advancements.
Challenges of Digitizing Reality into a Connected Metaverse – the Complexity of Data Requirements of Distributed Digital Twins
The integration of distributed digital twins within a metaverse represents a formidable challenge, particularly in terms of requirements setting and validation, of AI analytics and insights. Digital twins, which serve as virtual representations of physical entities, must continuously evolve to reflect changes in their real-world counterparts. These changes necessitate adjustments in interconnected digital twins, resulting in a dynamic and inherently unstable system. The primary challenge lies in ensuring the stability and predictability of these digital twins, which are essential for accurate and reliable interactions within the metaverse. I this talk, we will define the problem definition for a collaborative multi-party requirements management system for such metaverse conditions. It is also suggested to address the alignment challenge of a digital twins’ versioning by employing a web3 distributed ledger technology that can ensure confidentiality and privacy between participating parties, yet alert on potential compatibility and predictability issues.
Program - TBD
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