Keynote Speakers
Giancarlo Guizzardi
University of Twente, The Netherlands
Giancarlo Guizzardi is a Full Professor of Software Science and Evolution as well as Chair and Department Head of Semantics, Cybersecurity & Services (SCS) at the University of Twente, The Netherlands. He is also an Affiliated/Guest Professor at the Department of Computer and Systems Sciences (DSV) at Stockholm University, in Sweden. He has been active for nearly three decades in the areas of Formal and Applied Ontology, Conceptual Modelling, Business Informatics, and Information Systems Engineering, working with a multi-disciplinary approach in Computer Science that aggregates results from Philosophy, Cognitive Science, Logics and Linguistics. Over the years, he has delivered keynote speeches in several key international conferences in these fields. He is currently an associate editor of a number of journals including Applied Ontology and Data & Knowledge Engineering, a co-editor of the Lecture Notes in Business Information Processing series, and a member of several international journal editorial boards. He is also a member of the Advisory Board of the International Association for Ontology and its Applications (IAOA), and fellow of the most important scientific international community in Conceptual Modelling (https://conceptualmodeling.org/ER_Fellows.html).
Keynote Title: Carving Reality at its Digital Joints
Abstract: We live much of our lives immersed in the world of made-up structures that we call Social Reality. In other words, much of our lives are governed by socially constructed (and, hence, to a certain extent fictional) entities such as money, citizenships, employments, enrolments, marriages, presidential mandates, legal liabilities, stock options and derivative transactions, etc. With the massive advance of information technology, much of social reality is now purely grounded in a world of symbolic manipulation of digital representations. Moreover, much of this digital existence is scattered in several independent information silos that were created in different organizational cultures, through independent engineering processes, in different moments in space and time. Finally, we are more and more delegating decisions that help to create social reality to autonomous artificial systems. This scenario raises several critical questions, for example: how can we create a unified view of social reality by putting together pieces of information that now reside in independent information silos, each of which potentially carving out reality in potentially different ways? How can we build autonomous information systems that we understand and trust, i.e., systems that reflect our values, and that are semantically transparent and able to explain their decisions? In this talk, I intend to argue that modern information systems engineering cannot succeed without the support of the 2400 years-old discipline of Ontology in philosophy, a discipline devoted to the systematic investigation of what exists in a system of representations.
Chris Mitchell
Royal Holloway, University of London
Chris Mitchell has been a Full Professor at Royal Holloway, University of London since 1990, and has served as Head of Department of both Computer Science (1990-95) and Information Security (2021-23). He has worked in cryptography and information security for 45 years and has published over 250 papers in refereed journals and conference proceedings. He gained his PhD in 1979 from the University of London, and between 1979 and 1990 worked in industrial R&D at Racal Comsec and Hewlett-Packard. After joining Royal Holloway he co-founded the Information Security Group in 1990, and helped launch the MSc in Information Security in 1992. He has been co-editor-in-chief of Designs, Codes and Cryptography since 2011, and until 2021 was section editor for Section D of The Computer Journal. Between 2003 and 2014 he served as a member of Microsoft's Trustworthy Computing Academic Advisory Board.
Keynote Title: Out with the old: The cryptographic revolution caused by the threat of quantum computing
Abstract: Since its invention in the 1970s, public key cryptography has become a key security enabler: on the Internet, within enterprises, and enabling widespread secure communications. The benefits it brings in terms of enabling secure interoperation between entities with no prior relationship have been great, but came at a significant cost - public key cryptography has always been more computationally intensive than traditional secret key cryptography. Nonetheless, by the early 2000s - thanks to a range of innovations - we were in a world where standardised public key cryptography was very widely available. However, If and when large-scale general-purpose quantum computers are constructed, the effect on currently used public key cryptography will be very significant. In particular, Shor’s algorithm (published in 1994) has a very major impact on the security of all today’s widely used public key cryptography. This has led to large scale projects to develop new and practical techniques which will remain secure even in the presence of a quantum computer. Thanks to very major efforts across the cryptographic community, standards for new schemes are emerging which are already beginning to replace the vulnerable algorithms. This talk will explore the latest development and also the implications of this cryptographic revolution.
Liangxiu Han
Manchester Metropolitan University
Prof. Liangxiu Han has a PhD in Computer Science from Fudan University, Shanghai, P.R. China (2002). Prof. Han is currently a full Professor of Computer Science at the Department of Computing and Mathematics, Faculty of Science and Engineering, Manchester Metropolitan University. Prof. Han is Faculty Lead for AI, Digital and Cyber Physical Systems and Deputy Director of ManMet Crime and Well-Being Big Data Centre. Prof. Han’s research areas mainly lie in the development of novel big data analytics/Machine Learning/AI, and development of novel intelligent architectures that facilitates big data analytics (e.g., parallel and distributed computing, Cloud/Service-oriented computing/data intensive computing) as well as applications in different domains (e.g. Precision Agriculture, Health, Smart Cities, Cyber Security, Energy, etc.) As a Principal Investigator (PI) or Co-PI, Prof. Han has a proven track record of successfully leading multi-million-pound projects on both national and international scales (supported by diverse funding sources: UKRI, GCRF/Newton, EU, Industry, and Charity) and has extensive research and practical experiences in developing intelligent data driven AI solutions for various application domains (e.g. Health, Food, Smart Cities, Energy, Cyber Security) using various large datasets (e.g. images, numerical values, sensors, geo-spatial data, web pages/texts). Prof. Han has served as an associate editor/a guest editor for a number of reputable international journals and a chair (or Co-Chair) for organisation of a number of international conferences/workshops in the field. She has been invited to give a number of keynotes and talks on different occasions (including international conferences, national and international institutions/organisations). Prof. Han is a member of EPSRC Peer Review College, an independent expert of European Commission for proposal evaluation/mid-term project review, and British Council Peer Review Panel.
Keynote Title: Meeting Societal Challenges: Scalable Big Data-driven, AI- enabled Approaches
Abstract: By 2025, the total size of digital data generated by social networks, sensors, biomedical imaging and simulation devices, will reach an estimated 163 Zettabytes (e.g. 163 trillion gigabytes) according to IDC report. This type of 'big data', together with the advances in information and communication technologies such as data analytics/machine learning/AI, Internet of things (IoT), connected smart objects, wearable technology, ubiquitous computing, is transforming every aspect of modern life and bringing great challenges and spectacular opportunities to fulfil our dream of a sustainable smart society. This talk will focus on our latest developments and methods on scalable learning from large scale data and present real case studies to demonstrate how we applied big data driven, AI-enabled approaches in various application domains such as Health, Food to address society challenges.
John Shalf
Lawrence Berkeley National Laboratory
John Shalf is the Department Head for Computer Science at Lawrence Berkeley National Laboratory. He also formerly served as the Deputy Director for Hardware Technology on the US Department of Energy (DOE)-led Exascale Computing Project (ECP) before he returned to his department head position at LBNL. He has co-authored over 100 peer-reviewed publications in parallel computing software and HPC technology, including the widely cited report “The Landscape of Parallel Computing Research: A View from Berkeley” (with David Patterson and others). He is also the 2024-2027 distinguished lecturer for the IEEE Electronics Packaging Society. Before joining Berkeley Laboratory, John worked at the National Center for Supercomputing Applications and the Max Planck Institute for Gravitation Physics/Albert Einstein Institute (AEI), where he co-created the Cactus Computational Toolkit.
Keynote Title: Investigating Chiplets for Scalable and Cost Effective HPC Beyond Exascale
Abstract: Chiplets have become a compelling approach to scaling and heterogeneous integration e.g. integrating workload-specific processors and massive bandwidth memory systems into computing systems; integrating die from multiple function-optimized process nodes into one product; integrating silicon from multiple businesses into one product. Chiplet-based products have been produced in high volume by multiple companies using proprietary chiplet ecosystems. Recently, the community has proposed several new standards (e.g., UCIe) to facilitate integration and interoperability of any compliant chiplet. Hyperscalers (e.g., Google, Amazon) are actively designing high volume products with chiplets through these open interfaces. Other communities are exploring the end-to-end workflow and tooling to assemble chiplet-based products. High performance computing can benefit from this trend. However, the performance, power, and thermal requirements unique to HPC, present many challenges to realizing a vision for affordable, modular HPC using this new approach.