Keynote Speakers

Keynote Speakers

TBA

Professor Angelo Cangelosi

University of Manchester and Alan Turing Institute, UK

Title: Developmental Robotics for Language Learning, Trust and Theory of Mind

Abstract: Growing theoretical and experimental research on action and language processing and on number learning and gestures clearly demonstrates the role of embodiment in cognition and language processing. In psychology and neuroscience, this evidence constitutes the basis of embodied cognition, also known as grounded cognition (Pezzulo et al. 2012). In robotics and AI, these studies have important implications for the design of linguistic capabilities in cognitive agents and robots for human-robot collaboration, and have led to the new interdisciplinary approach of Developmental Robotics, as part of the wider Cognitive Robotics field (Cangelosi & Schlesinger 2015; Cangelosi & Asada 2022). During the talk we will present examples of developmental robotics models and experimental results from iCub experiments on the embodiment biases in early word acquisition and grammar learning (Morse et al. 2015; Morse & Cangelosi 2017) and experiments on pointing gestures and finger counting for number learning (De La Cruz et al. 2014). We will then present a novel developmental robotics model, and experiments, on Theory of Mind and its use for autonomous trust behavior in robots (Vinanzi et al. 2019, 2021). The implications for the use of such embodied approaches for embodied cognition in AI and cognitive sciences, and for robot companion applications will also be discussed.

Short Bio: Angelo Cangelosi is Professor of Machine Learning and Robotics at the University of Manchester (UK) and co-director and founder of the Manchester Centre for Robotics and AI. He was selexcted for the award of the European Research Council (ERC) Advanced grant (funded by UKRI). His research interests are in cognitive and developmental robotics, neural networks, language grounding, human robot-interaction and trust, and robot companions for health and social care. Overall, he has secured over £38m of research grants as coordinator/PI, including the ERC Advanced eTALK, the UKRI TAS Trust Node and CRADLE Prosperity, the US AFRL project THRIVE++, and numerous Horizon and MSCAs grants. Cangelosi has produced more than 300 scientific publications. He is Editor-in-Chief of the journals Interaction Studies and IET Cognitive Computation and Systems, and in 2015 was Editor-in-Chief of IEEE Transactions on Autonomous Development. He has chaired numerous international conferences, including ICANN2022 Bristol, and ICDL2021 Beijing. His book “Developmental Robotics: From Babies to Robots” (MIT Press) was published in January 2015, and translated in Chinese and Japanese. His latest book “Cognitive Robotics” (MIT Press), coedited with Minoru Asada, was recently published in 2022.

Professor Haris Mouratidis

Director of Institute for Analytics and Data Science – IADS, Professor of Data Science and Statistics, School of Computer Science and Electronic Engineering, University of Essex, UK

Title: AI and cybersecurity: Friend or Foe?

Abstract: We live in an era of unprecedented technological advancement that has an impact on every aspect of the human life. Within that environment, artificial intelligence and cybersecurity are two areas where innovation and challenges intersect with profound implications. On one hand, AI, with its transformative capabilities, is revolutionising how we process information, make decision and interact with technology, while on the other hand, cybersecurity provides essential tools to safeguard the digital infrastructures that we depend on.

In this talk I will discuss the interplay between the two, exploring both the benefits of using AI for cybersecurity and cybersecurity for AI, but also the challenges that such co-existence introduces. Drawing on real-world case studies and insights, I will discuss how machine learning, threat detection and analytics can empower organisations and individuals to improve their cybersecurity but also how AI-driven tactics give rise to sophisticated cyber threats. I will then emphasize the necessity for collaborative initiatives spanning both AI and cybersecurity domains. I will stress the importance of continuous shared research and education to foster an environment where the coexistence of AI and cybersecurity not only enhances our digital landscape but also minimizes associated risks

Short Bio: Haralambos (Haris) Mouratidis is Professor and Director of the Institute for Analytics and Data Science (IADS) at the University of Essex. Before, he was professor of secure software engineering and founding director of the Centre for Secure, Intelligent and Usable System (CSIUS) at the University of Brighton. His research interests include cybersecurity data science (with focus on AI and machine learning and data analytics for cybersecurity risk management, threat modelling and data protection), intelligent data security engineering (with focus on the development of novel methodologies and techniques to improve privacy by design and security by design and AI-enabled model based security engineering), and Threat modelling and privacy protection for AI and data science (with focus on adversarial attacks on machine learning and machine learning facilitated adversarial mechanisms). He has published more than 210 papers and he has secured funding of c.£30M, funded mostly by the UK and the EU. He is Fellow of the UK Higher Education Academy and “Standards-maker” of the British Standards Institution for the “Privacy-By-Design” and “Software and Systems Engineering” national committees. He is elected Vice-Chair of the IFIP WG on Secure Engineering, Expert Fellow of the UK Digital Economy Network Plus, on the register of ENISA’s experts and was member of the ENISA WG on European Cybersecurity Skills Framework (ECSF). He has been invited subject expert for events organised by national and international organisations (e.g. EU, NATO); more recently he spoke about AI-driven Privacy-by-Design, on an event organised by the European Commission and led discussion on challenges of Automated Software Engineering towards GDPR compliance at a meeting organised by the European Research Executive Agency.

Professor Emma Hart

FRSE, Professor at Edinburgh Napier University, Edinburgh, Scotland, United Kingdom

Title: An Evolutionary Approach to the Autonomous Design and Fabrication of Robots for Operation in Unknown Environments

Abstract: Robot design is traditionally the domain of humans – engineers, physicists, and increasingly AI experts. However, if the robot in intended to operate in a completely unknown environment (for example clean up inside a nuclear reactor) then it is very difficult for human designers to predict what kind of robot might be required. Evolutionary computing is a well-known technology that has been applied in various aspects of robotics for many years, for example to design controllers or body-plans. When coupled with advances in materials and printing technologies that allow rapid prototyping in hardware, it offers a potential solution to the issue raised above, for example enabling colonies of robots to evolve and adapt over long periods of time while situated in the environment they have to work in. However, it also brings new challenges, from both from an algorithmic and engineering perspective.

The additional constraints introduced by the need for example to manufacture robots autonomously, to explore rich morphological search-spaces and develop novel forms of control require some re-thinking of “standard’ approaches in evolutionary computing, particularly on the interaction between evolution and individual learning.  I will discuss some of these challenges and propose and showcase some methods to address them that have been developed in during a recent project

Short Bio:

Education

  • PhD University of Edinburgh, 2002 “Artificial Immune Systems as a Metaphor for Information Processing: Fact or Fiction”
  • MSc University of Edinburgh, 1995, Knowledge Based Systems (with distinction)
  • BA (Hons) University of Oxford, 1990, Chemistry (1st class)
Funding Awarded
  • RSIE: F1 £11,500 (2020). Guided Self-Organisation in Swarm Robotics
  • Leverhulme: F2 £34,500 (2015) Research Fellowship: Ensembles for Optimisation
  • EPSRC: F3: £380,000 (2021-2025) Keep-Learning [PI] (part of £760,000 collaborative project), F4: £1,346,885 (2020-2024) COG-HEAR: Towards cognitively inspired 5G-IoT enabled multi- modal Hearing Aids (part of £3.2 million collaborative project), F5: £366,41 (2018-2022) Autonomous Robots: from Cradle to Grave (part of a £1.8 Million project across 3 universities). (PI), F6: £238,068 (2012-2015) Real-World Optimisation with Lifelong Learning (PI), F7: £62, 564 (2005) ARTIST: A Network for Artificial Immune Systems (CoI), F8: £256, 547 (2002) Hyper-Heuristics.
  • EU: F9: FOCAS: €461086 (2013) Rated Excellent. (PI), F10: AWARE: €457,900 EUR (2010) Rated Excellent. (PI), F11: PerAda €727,632 EUR (2008) Rated Excellent (CoI), F12: SIGNAL €299,196 EUR (2004).
  • UKRI: Knowledge Transfer Projects: F13 £268,152 (2018-2021) Improving Customer Experience through AI assisted intelligent workflows,  F14 £89,470 (2014-2016): Optimization for Structural Design (PI)
  • Datalab: F15 £20,000 Infrastructure Optimisation (2020)
Awards/Honours
  • ACM Outstanding Contribution To Evolutionary Computing (2023)
  • Fellow of the Royal Society of Edinburgh (elected March 2022)
  • Bronze Award GECCO 2018
  • Best Paper Awards: GECCO 2018, 2019, IEEE Self- Organizing and Self-Adaptive Systems, SASO 201.
  • GENOPT 2016 Prize, Biathlon and High Jump: Eduardo Segredo, Eduardo Lalla-Ruiz, Ben Paechter, Emma Hart, Stefan Voß
  • Invited participant in Royal Society Frontiers of Science Exchange with Russian Academy of Sciences in Kazan, Russia, representing UK Computer Science UK 2013
Keynote Speeches at International Conferences:
  • EURO Distinguished Lecture, CLAIO2022, Argentina (December 2022)
  • IEEE Congress on Evolutionary Computing, Italy, 2022
  • UK Conference on Computational Intelligence (UKCI 2021):
  • IEEE Congress on Evolutionary Computing, New Zealand, 2019: Towards the Autonomous Evolution of Robotic Ecosystems
  • IEEE International Joint Conference on Computational Intelligence (Madeira, 2017): Towards Lifelong Learning in Optimisation
  • 28th Conference on Operational Research (EURO 2016, Poland): Lifelong learning for optimisation
  • 5th UK Conference on Computational Intelligence (UKCI 2015): Hyper-heuristics for life-long optimisation Women@GECCO, Genetic and Evolutionary Computation Conference, Madrid
  • Fully funded invited talks in 7 other countries
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