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Prof. Amin Beheshti Full Professor of Data Science and the Director of AI-enabled Processes (AIP) Research Centre, School of Computing, Macquarie University email: amin.beheshti@mq.edu.au |
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Biography:
Prof. Dr. Amin Beheshti is a Full Professor of Data Science at Macquarie University, and Adjunct Professor of Computer Science at UNSW Sydney, Australia. Amin is the founder and director of the Centre for Applied Artificial Intelligence, the head of the Data Science Lab, and the founder of the Big Data Society at Macquarie University, Sydney, Australia. Amin completed his PhD and Postdoc in Computer Science and Engineering at UNSW Sydney, and holds a Master's and Bachelor's degree in Computer Science, both with First Class Honours. Before starting his PhD in 2009, Amin had over a decade of industry experience as a founder and CEO, consultant, and Solution Architect in national and international organizations. Alongside his teaching activities, Amin has made significant contributions to research projects and successfully secured 40+ research projects (Over $29 million in Research Funding). Amin received prestigious awards, including Excellence Award (Macquarie University, 2023), Excellence in Research Innovation, Partnership Entrepreneurship (Macquarie University, 2022), National Security Impact Award (D2D CRC, 2016 and 2017), Recognition Award (D2D CRC, 2016 and 2017), Australian Postgraduate Award (APA 2009-2012), and several Best Paper awards. In 2021, due to his outstanding performance, Amin was promoted from Senior Lecturer to Full Professor at Macquarie University. As a distinguished researcher in Data and AI Science, Amin has been invited to serve as a Keynote Speaker, General-Chair, PC-Chair, Organisation-Chair, and program committee member of top international conferences. He is also a leading author of several authored books in data, social, and process analytics, co-authored with other high-profile researchers.
Title of Speech:
Exploring the Convergence of Internet of Things and Big Data Technologies in the Age of Generative Artificial Intelligence
Abstract:
In this keynote, we explore the convergence of the Internet of Things (IoT) and Big Data Technologies in the context of Generative Artificial Intelligence (GenAI), highlighting their synergistic impact on enhanced data generation and analysis, personalization, and predictive modelling. This integration drives innovation and efficiency across sectors, particularly in applications like smart cities and healthcare, where GenAI leverages the wealth of data for optimized decision-making and personalized solutions. We will also address the challenges, especially in data privacy and security, emphasizing the need for ethical frameworks in GenAI development. This convergence is not just a technological milestone but a transformative force in the evolution of AI, offering unprecedented opportunities for advancement while underscoring the importance of responsible AI application.
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Prof. Raja Jurdak Professor of Distributed Systems & Chair in Applied Data Sciences, as well as the Director of the Trusted Networks Lab at Queensland University of Technology email: r.jurdac@qut.edu.au |
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Biography:
Prof. Dr. Raja Jurdak is a Professor of Distributed Systems and Chair in Applied Data Sciences at Queensland University of Technology, where he is Director of the Trusted Networks Lab. He received the PhD in information and computer science from the University of California, Irvine. He previously established and led the Distributed Sensing Systems Group at CSIRO’s Data61, where he maintains a visiting scientist role. He also spent time as visiting academic at MIT and Oxford University in 2011 and 2017. His research interests include trust, mobility and energy-efficiency, and cybersecurity in networks. Prof. Jurdak has published over 250 peer-reviewed publications, including three authored books. He serves on the editorial board of Ad Hoc Networks, and on the organising and technical program committees of top international conferences, including Percom, ICBC, IPSN, WoWMoM, and ICDCS. He is an Adjunct Professor with the University of New South Wales, a Distinguished Visitor of the IEEE Computer Society, and a Senior Member of the IEEE.
Title of Speech:
Title: Blockchain for Cyber-physical Systems
Abstract:
Cyber-physical systems (CPS) encompass a broad range of devices capable of sensing the environment and communicating with other users or devices. Heterogeneity of the devices, low resource availability, no or limited built-in security safeguards, centralized communication infrastructure, and large volumes of personalized data collected by the devices emphasise the trust, security and privacy challenges in CPS. In recent years, blockchain has attracted tremendous attention to address the outlined challenges due to its salient features including decentralization, anonymity, security, trust, and auditability.
This talk will discuss our work on blockchain for CPS. It first discusses the challenges in existing CPS architectures, including scalability, trust, and storage optimisation. This talk will explore the role of blockchain in addressing these challenges, along with blockchain design considerations that are pertinent for its application in CPS. Finally, the talk will cover blockchain applications in CPS that we have targeted.
