Zoom link for the keynotes: https://zu-ac-ae.zoom.us/j/97702866406
Davor Svetinovic
Khalifa University , UAE
Title: Beyond Blockchain Censorship
Abstract:
This talk will present and expand beyond our recent published work on Blockchain Censorship. First, we’ll present how despite permissionless blockchains are designed to be resilient against censorship by any single entity. They are relying on deterministic rules rather than third-party actors to determine whether a transaction is added to the blockchain. However, in 2022, the U.S. Office of Foreign Assets Control (OFAC) sanctioned a Bitcoin mixer and an Ethereum application, challenging this presumed neutrality. In this paper, we formalized, quantified, and analyzed the security implications of blockchain censorship. We began by defining censorship and then conducted a quantitative assessment of current censorship practices. Our analysis revealed that 46% of Ethereum blocks were produced by entities complying with OFAC sanctions, highlighting the substantial influence of these sanctions on the neutrality of public blockchains. Furthermore, we found out that censorship not only undermines neutrality but also compromises security. Following Ethereum's transition to Proof-of-Stake (PoS), censored transactions experienced an average delay of 85%, weakening their security and increasing the vulnerability to sandwich attacks. We will also present our most recent advances that build upon our Blockchain Censorship paper [https://dl.acm.org/doi/10.1145/3589334.3645431]
Biography:
Davor Svetinovic is a professor of computer science at Khalifa University, Abu Dhabi He received his doctorate in computer science from the University of Waterloo, Waterloo, ON, Canada, in 2006. Previously, he worked at WU Wien, TU Wien, Austria, and Lero - the Irish Software Engineering Center, Ireland. He was a visiting professor and a research affiliate at MIT and MIT Media Lab, MIT, USA. Davor has extensive experience working on complex multidisciplinary research projects. He is a highly cited researcher in cybersecurity and blockchain technology. His research interests include cybersecurity, blockchain technology, cryptoeconomics, trust, and software engineering. His career has furthered his interest and expertise in developing advanced research capabilities and institutions in emerging economies. He is a Senior Member of IEEE and ACM (Lifetime) and a Mohammed Bin Rashid Academy of Scientists affiliate.
Samson Lasaulce
Chief Research Scientist, Khalifa University, UAE
Title: LLMs, optimization, and game theory
Abstract:
In this talk, we will explore the interplay between large language models (LLMs) and optimization. After introducing a use case (consumption power scheduling) for which studying this interplay is fully relevant, we will survey the main approaches in this area, which include pure LLM-based approaches (e.g., to deal with mathword problems) and combined approaches. Both limitations and promising solutions will be discusssed. In the last part of the talk, connections between LLMs and game theory will be discussed.
Biography:
Samson Lasaulce is a Chief Research Scientist with Khalifa University. He is the holder of the TII 6G Chair on Native AI. He is also a CNRS Director of Research with CRAN at Nancy. He has been the holder of the RTE Chair on the "Digital Transformation of Electricity Networks". He has also been a part-time Professor with the Department of Physics at École Polytechnique (France). Before joining CNRS he has been working for five years in private R&D companies (Motorola Labs and Orange Labs). His current research interests lie in distributed networks with a focus on optimization, game theory, and machine learning. The main application areas of his research are wireless networks, energy networks, social networks, and now climate change. Dr Lasaulce has been serving as an editor for several international journals such as the IEEE Transactions. He has organized many scientific events and 10+ as a general chair. He is the co-author of more than 200 publications, including a dozen of patents and several books such as "Game Theory and Learning for Wireless Networks: Fundamentals and Applications". Dr Lasaulce is also the recipient of several awards such as the Blondel Medal award from the SEE French society.
Albert Zomaya
University of Sydney, Australia
Title: Generative AI at the Edge: Enhancing Local Data Processing for Real-Time Applications
Abstract:
Edge computing is reshaping the landscape of data processing by moving computation closer to where data is generated, reducing the need for costly data transfers to cloud servers. As the demand for real-time, privacy-sensitive applications grows, generative Artificial Intelligence (AI) has emerged as a powerful tool to complement edge computing. This talk explores the potential of deploying generative AI models, such as Large Language Models, on edge devices to deliver advanced local data processing and content generation. The session addresses the unique challenges of deploying AI in resource-constrained environments, including optimizing models for limited computational power, managing network bandwidth efficiently, and preserving data privacy. Additionally, the presentation highlights real-world applications of generative AI at the edge, such as personalized healthcare monitoring, autonomous vehicles, smart manufacturing, and predictive maintenance. By examining emerging techniques for distributed learning and AI model optimization, this talk demonstrates how generative AI can unlock new capabilities for edge-based applications, enhancing both efficiency and functionality in a wide range of industries.
Biography:
Albert Zomaya is the Peter Nicol Russell Chair Professor of Computer Science and Director of the Centre for Distributed and High-Performance Computing at the University of Sydney. To date, he has published > 800 scientific papers and articles and is (co-)author/editor of >30 books. A sought-after speaker, he has delivered >300 keynote addresses, invited seminars, and media briefings. He is the past Editor in Chief of the IEEE Transactions on Computers (2010-2014), the IEEE Transactions on Sustainable Computing (2016-2020), and the ACM Computing Surveys (2019-2024).
Professor Zomaya is a decorated scholar with numerous accolades, including Fellowships of the IEEE, the American Association for the Advancement of Science, and the Institution of Engineering and Technology. Also, he is a Fellow of the Australian Academy of Science, Royal Society of New South Wales, a Foreign Member of Academia Europaea, and a Member of the European Academy of Sciences and Arts.
Some of Professor Zomaya's recent awards include the Research Innovation Award, the IEEE Computer Society’s Technical Committee on Cloud Computing (2021), the Technical Achievement and Recognition Award, IEEE Communications Society’s IoT, Ad Hoc, and Sensor Networks Technical Committee (2022), and the Distinguished Technical Achievement Award, IEEE Communications Society’s Technical Committee on Big Data (2024). Professor Zomaya is a Clarivate 2022&2023 Highly Cited Researcher, and his research interests lie in parallel and distributed computing, networking, and complex systems.
Berick Cook
AI Developer, SingularityNET
Title: Autonomous Intelligent Reinforcement Interpreted Symbolism (AIRIS): Beyond Reinforcement Learning
Abstract:
In this Workshop we will be discussing how Autonomous Intelligent Reinforcement Interpreted Symbolism (AIRIS) differs from traditional Reinforcement Learning, and the significant advantages it affords. We will also explore the current state of research and future research directions that will be pursued. Lastly we will venture into the hypothetical with potential use cases that can be unlocked as development continues and AIRIS integrates into the Primus cognitive architecture powered by OpenCog Hyperon.
Biography:
Biography:
Berick Cook is a independent videogame developer turned AI researcher and the creator of AIRIS (Autonomous Intelligent Reinforcement Inferred Symbolism). Originally from Alaska, he honed his skills through self-directed learning, enabling him to pursue his passions.
In 2016, he began working on AIRIS as a way to bring more life into game characters by giving them a way to learn their intended behavior rather than requiring handcrafted code. Seeing how effective the method was, he worked to expand the concept into other domains such as simple computer vision and rudimentary robotic control. In March of 2024 he joined SingularityNet to further develop the concept and take it beyond game worlds as a practical alternative to traditional Reinforcement Learning.