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Emotionally Intelligent Computing

There is broad belief that emotions, thinking, and learning are linked and Goleman's EQ perspective on emotional intelligence names empathy, effective communication or social skills, self-awareness, self-regulation, and motivation as core skills. So how about lending AI EQ? For that, in this talk, the state-of-play in Affective Computing – the science of computing and emotions or more broadly speaking affect – will be presented in a nutshell. This includes the analysis and synthesis of emotions in human and general multimodal data such as audio, video, text, and physiological data. Furthermore, a perspective on using emotions in machine learning will be given. As the field is also impacted by the advent of large “foundation models” and their emergent behaviour, a view on the future of Affective Computing and its role in Emotionally Intelligent Computing will conclude the talk. Computers can already “be” empathetic and simulate social skills – is the rest yet to come?

Björn W. Schuller

Imperial College London, UK

　　Björn W. Schuller received his diploma, doctoral degree, habilitation, and Adjunct Teaching Professor in Machine Intelligence and Signal Processing all in EE/IT from TUM in Munich/Germany. He is Full Professor of Artificial Intelligence and the Head of GLAM at Imperial College London/UK, Full Professor and Chair of Embedded Intelligence for Health Care and Wellbeing at the University of Augsburg/Germany, co-founding CEO and current CSO of audEERING – an Audio Intelligence company based near Munich and in Berlin/Germany, independent research leader within the Alan Turing Institute as part of the UK Health Security Agency, and permanent Visiting Professor at HIT/China amongst other Professorships and Affiliations. Previous stays include Guest Professor at Southeast University in Nanjing/China, Full Professor at the University of Passau/Germany, Key Researcher at Joanneum Research in Graz/Austria, and the CNRS-LIMSI in Orsay/France. He is a Fellow of the IEEE and Golden Core Awardee of the IEEE Computer Society, Fellow of the BCS, Fellow of the ELLIS, Fellow of the ISCA, Fellow and President-Emeritus of the AAAC, Elected Full Member Sigma Xi, and Senior Member of the ACM. He (co-)authored 1,200+ publications (50,000+ citations, h-index=100+ ranking him number 7 in the UK for Computer Science), is Field Chief Editor of Frontiers in Digital Health and was Editor in Chief of the IEEE Transactions on Affective Computing amongst manifold further commitments and service to the community. His 50+ awards include having been honoured as one of 40 extraordinary scientists under the age of 40 by the WEF in 2015. He served as Coordinator/PI in 15+ European Projects, is an ERC Starting and DFG Reinhart-Koselleck Grantee, and consultant of companies such as Barclays, GN, Huawei, Informetis, or Samsung. Schuller counts more than 300 public press appearances including in Business Insider, Guardian, International Business Times, Newsweek, Scientific American, Times, The Economist 1843, UK Daily Mail, and national and international podcast, radio, and television contributions such as in MIT Technology Review and “The World” and “The Why”. 　　

Keynote Talk

Towards General Purpose Brain Inspired Computing

The current computer is the key to build the digital universe. Over the past half century, the driven force to develop computers with von Neumann architecture have been being scaling, which follows Moore's law. We are now approaching the physical limitation of scaling. One of the most promising way for the further development of computers is to develop brain-inspired computing (BIC). Although great efforts have been put into the development of BIC, there is yet to be a commonly accepted technological solution. In this talk, the recent progress in the development of BIC is reviewed, which includes BIC theory, chips, software, systems and applications. The main challenge, and possible solutions to develop BIC system are addressed. The key issues to develop general purpose BIC are also discussed.

Luping Shi

Tsinghua University, China

Keynote Talk

Symbiotic Autonomy: Integrating AI and Humans and Learning from Experience

In this talk, I will present work on novel human-AI interaction, in which humans and AI complement each other in their knowledge and learning. I will discuss examples in autonomous mobile service robots and in the financial domain. I will conclude with a brief discussion of multiple forms of available knowledge for AI to continuously learn from experience.

Manuela Veloso

J.P. Morgan Chase AI Research, USA

Keynote Talk

Materials-GPT—Domain Knowledge-Guided Materials AI Experiments and Computations

This presentation briefly introduces the concept of Materials Informatics and Materials-GPT. Materials informatics is growing extremely fast by integrating Artificial Intelligence (AI) and machine learning with materials science and engineering to accelerate materials science, engineering and manufacturing innovations. Particularly, the birth of Chat-GPT-4 further pours oil on the flames of Materials Informatics and hastens the parturition of Materials-GPT. Two fundamentals are there in Materials-GPT, including materials AI robots and AI labs, and materials AI computations and AI software and the both “hard” and “soft” fundamentals must be very strong and developed under the guidance of domain knowledge, which will result in materials large multimodal model. The domain knowledge-guided machine learning strategy is the best way to create new knowledge, innovate and progress materials science and engineering, and speed up the materials manufacturing. Case studies are given on the oxidation behaviours of ferritic-martensitic steels in supercritical water and the oxidation behaviours of FeCrAlCoNi based high entropy alloys at high temperature. This strategy leads to the development of formulas with high generalization and accurate prediction power, which are most desirable to science, technology, and engineering.