CERN Accelerating science

Raia Hadsell is the Director of Robotics at DeepMind. Dr. Hadsell joined DeepMind in 2014 to pursue new solutions for artificial general intelligence. Her research focuses on the challenge of continual learning for AI agents and robots, and she has proposed neural approaches such as policy distillation, progressive nets, and elastic weight consolidation to solve the problem of catastrophic forgetting. Dr. Hadsell is on the executive boards of ICLR (International Conference on Learning Representations), WiML (Women in Machine Learning), and CoRL (Conference on Robot Learning). She is a fellow of the European Lab on Learning Systems (ELLIS), a founding organizer of NAISys (Neuroscience for AI Systems), and serves as a CIFAR advisor.

Michael Doser is a research physicist at CERN, who has specialized in working with antimatter, using it either as a tool (to study the strong interaction), or as an object of study itself.

He is currently spokesperson of the AEGIS experiment, whose goal is to measure the gravitational interaction between matter and antimatter, which requires building bridges between particle physics and other research fields, such as atomic physics, gravitation, material science or physical chemistry. Michael is part of the Sparks Editorial Committee and is editor for Physics Letters B and for Review of Particle Physics.

Jaan Tallinn is a founding engineer of Skype and Kazaa. He founded the Centre for the Study of Existential Risk with Huw Price and Martin Rees. He is also a co-founder of the Future of Life Institute and philanthropically supports other existential risk research organizations.

He is also a partner at Ambient Sound Investments (asi.ee), an active angel investor, and has served on the Estonian President’s Academic Advisory Board. He has given a number of high-profile talks highlighting the potential risk from advances in artificial intelligence.

Maria Spiropulu is the Shang-Yi Ch’en Professor of Physics at Caltech. She received her PhD in physics from Harvard and was Enrico Fermi Fellow at the University of Chicago before moving to CERN. She worked at the Tevatron’s collider experiments and at the CERN’s LHC on detector and trigger R&D and searches for dark matter and other new physics including the discovery of the Higgs. Since 2013 she is exploring and applying AI and Quantum-AI to accelerate discovery in HEP and other domains. In 2017 she founded at Caltech the “INtelligent Quantum NEtworks and Technologies (In-Q-Net)  research program focusing on quantum networks and HEP/QIS intersections.

Spiropulu was the chair of the Fermilab Physics Advisory Committee and member of the High Energy Physics Advisory Panel to the U.S. Department of Energy and the National Science Foundation. She was a member of the Aspen Center for Physics,  the chair of of the Forum of International Physics of the American Physical Society and member of  the Advisory Panel of the HEP Forum for Computational Excellence.  She is the founder of the Physics of the Universe Summit  (POTUS) that explores challenges in emerging and cross-cutting areas of science and technology. She is a Fellow of the American Association for the Advancement of Science and the American Physical Society and was the Chair of the Caltech Faculty in 2019-20. 

Jürgen Schmidhuber is the Scientific Director of the Swiss AI Lab IDSIA in Switzerland, a Professor of Artificial Intelligence at the University of Lugano and the Co-founder and Chief Scientist of the company NNAISENSE, which aims at building the first practical general purpose AI. Since age 15 or so, his main goal has been to build a self-improving Artificial Intelligence (AI) smarter than himself, then retire. His lab's Deep Learning Neural Networks (such as LSTM) based on ideas published in the "Annus Mirabilis" 1990-1991 have revolutionised machine learning and AI.

In 2011, his team was the first to win official computer vision contests through deep neural nets, with superhuman performance. In 2012, they had the first deep NN to win a medical imaging contest (on cancer detection). This attracted enormous interest from industry. His research group also established the fields of metalearning, mathematically rigorous universal AI and recursive self-improvement in universal problem solvers that learn to learn (since 1987). He is recipient of numerous awards, author of over 350 peer-reviewed papers. He is a frequent keynote speaker, and advising various governments on AI strategies.

Stuart Russell is a Professor of Computer Science and Smith-Zadeh Professor in Engineering, University of California, Berkeley and Honorary Fellow, Wadham College, Oxford.

His book "Artificial Intelligence: A Modern Approach" (with Peter Norvig) is the standard text in AI; it has been translated into 14 languages and is used in over 1400 universities in 128 countries. His research covers a wide range of topics in artificial intelligence including machine learning, probabilistic reasoning, knowledge representation, planning, real-time decision making, multitarget tracking, computer vision, computational physiology, and philosophical foundations.

He also works for the United Nations, developing a new global seismic monitoring system for the nuclear-test-ban treaty. His current concerns include the threat of autonomous weapons and the long-term future of artificial intelligence and its relation to humanity. The latter topic is the subject of his new book, "Human Compatible: AI and the Problem of Control" (Viking/Pengun, 2019).

Francesca Rossi is the IBM AI Ethics Global Leader and an IBM fellow. Her research interests focus on artificial intelligence, specifically constraint reasoning, preferences, multi-agent systems, computational social choice, and collective decision making.

She is also interested in ethical issues in the development and behaviour of AI systems, in particular for decision support systems for group decision making. She co-chaired the AAAI committee on AI and ethics and she is a member of the scientific advisory board of the Future of Life Institute and of the Leverhulme Centre for the Future of Intelligence.

She is in the executive committee of the IEEE global initiative on ethical considerations on the development of autonomous and intelligent systems and she co-leads the World Economic Forum Council on AI for humanity. She is a member of the board of directors of the Partnership on AI and the president-elect of AAAI.

Tomaso Poggio is one of the founders of computational neuroscience. He pioneered a model of the fly’s visual system as well as of human stereovision. His research has always been interdisciplinary, bridging brains and computers. It is now focused on the mathematics of deep learning and on the computational neuroscience of the visual cortex.

Poggio also introduced using an approach called regularization theory to computational vision, made key contributions to the biophysics of computation and to learning theory, and developed an influential model of recognition in the visual cortex. Research in the Poggio lab is guided by the belief that understanding learning is at the heart of understanding both biological and artificial intelligence. Learning is therefore the route to understanding how the human brain works and for making intelligent machines.

Maja Pantic is a Professor of Affective and Behavioural Computing at Imperial College London and an AI Scientific Research Lead in Facebook London. She previously held the position of Professor of Affective and Behavioral Computing and leader of the i·BUG group and the Research Director of the Samsung AI Centre in Cambridge (SAIC), working on machine analysis of human non-verbal behaviour and its applications to human-computer, human-robot, and computer-mediated human-human interaction.

Prof. Pantic published more than 250 technical papers in the areas of machine analysis of facial expressions, machine analysis of human body gestures, audiovisual analysis of emotions and social signals, and human-centered machine interfaces. She has more than 25,000 citations to her work, and has served as the Key Note Speaker, Chair and Co-Chair, and an organization/ program committee member at numerous conferences in her areas of expertise.

Nyalleng is a research software engineer at Google working on topics related to ethics and fairness in machine learning. Before Google she was a senior researcher at the South African Council for Scientific and Industrial research, where she worked closely with government and academic institutions to develop products to understand phenomena such as Rhino poaching with the South African Park services and Election sentiment analysis with the South African Broadcasting Corporation and legacies of Spatial Aparthied with local faculty.

Outside of formal work she is involved in efforts to democratize AI; she is a founding member of the Deep Learning Indaba, the largest machine learning consortium of AI/ML practitioners in Africa, a member of A+ Alliance an international coalition that seeks to not only detect, but correct, gender bias in Artificial Intelligence.