Arrival & Champagne Reception
Sally Eaves - Forbes Technology Council
Sally combines a depth of experience as a Chief Technology Officer, Practising Professor of FinTech, Founder and Global Strategic Advisor, consulting on the application of disruptive technologies for both business and societal benefits. She is an award-winning thought leader in innovation, digital transformation and emergent technology, notably blockchain, artificial intelligence, machine learning and robotics. A member of the Forbes Technology Council, Sally is an accomplished author with regular contributions to leading business, technology and academic publications. She is an international keynote speaker and respected online influencer across multiple channels and consistently rated in the top 10 for blockchain and social media influence worldwide. Sally strongly believes in technology being an enabler for social good which is reflected in her recent shortlisting for the UK IT Woman of the Year Business Role Model Award alongside active roles as a STEM ambassador, trustee and mentor.
Silvia Chiappa - DeepMind
Machine learning is increasingly being used to take decisions that can severely affect people's lives, e.g. in policing, education, hiring, lending, and criminal risk assessment. However, most often the data used to train such decision systems contains bias that exists in our society. This bias can be absorbed or even amplified by the systems, leading to decisions that are unfair with respect to sensitive attributes (e.g. race and gender). In this talk, I will present the different ways in which the machine learning community is addressing the issue of fairness, and introduce a method for dealing with the complex scenario in which the sensitive attribute affects the decision through both fair and unfair pathways.
Silvia is a senior research scientist at DeepMind, where she works on deep models of high-dimensional time-series and algorithmic fairness, and also contributes to the DeepMind's diversity and inclusion initiative. Silvia received a Diploma di Laurea in Mathematics from University of Bologna and a PhD in Statistical Machine Learning from École Polytechnique Fédérale de Lausanne. Before joining DeepMind, she worked in several Machine Learning and Statistics research groups, such as the Empirical Inference Group at the Max-Planck Institute for Biological Cybernetics, the Machine Learning and Perception Group at Microsoft Research Cambridge, and the Statistical Laboratory at University of Cambridge. Silvia's research interests are based around Bayesian and causal reasoning, approximate inference, time-series models, and deep learning.
Cecilia Mascolo - University of Cambridge & The Alan Turing Institute
Enabling Learning on Mobile and Wearables: Challenges and Opportunities
With the advent of powerful and inexpensive sensing technology the ability to study human behaviour and activity at large scale and for long periods has in theory become reality. As a consequence data scientists have started to produce mobile tools to increase disease monitoring.In this talk Cecilia will initially describe her research in the area of mobile systems and mobile data analytics. She will then illustrate the challenges and opportunities of this research with respect bringing the logic and learning on device and close to the user: this will include aspects related to processing and power challenges. Cecilia will close by talking about the applications of these approaches to a variety of disciplines including health and urban computing.
Cecilia Mascolo is a Full Professor of Mobile Systems in the Computer Laboratory, University of Cambridge, UK, a Fellow of Jesus College Cambridge and a Faculty Fellow at the Alan Turing Institute for Data Science in London. Prior joining Cambridge in 2008, she has been a faculty member in the Department of Computer Science at University College London. She holds a PhD from the University of Bologna. Her research interests are in human mobility modelling, mobile and sensor systems and networking and spatio-temporal data analysis. She has published in a number of top tier conferences and journals in the area and her investigator experience spans projects funded by Research Councils and industry. She has received numerous best paper awards and in 2016 was listed in “10 Women in Networking /Communications You Should Know”. She has served as organizing and programme committee member of mobile, sensor systems, networking, data science conferences and workshops. She has delivered a number of keynote talks at conferences and workshops in the area of mobility, data science, pervasive computing and systems. She is associate editor in chief for IEEE Pervasive Computing and has/is sitting on the editorial boards of IEEE Transactions on Mobile Computing, ACM Transactions on Sensor Networks and ACM Transactions on Interactive, Mobile, Wearable and Ubiquitous Technologies, IEEE Internet Computing. More details at www.cl.cam.ac.uk/users/cm542.
Marian Nicholson - Fujitsu
AI & Image Recognition Technology
Combining AI-based image recognition technology with high-speed image processing technology cultivated with supercomputer technology makes it possible to capture images from surveillance cameras located over a wide area that cannot be grasped by human visual observation. This technology enables assessment of the movements of people and vehicles throughout a city, thereby helping to prevent crime and optimise the urban lifestyle. By watching over entire cities, this can be a force for good or the realisation of the 1984 future, foretold by George Orwell. This short talk focuses on the use of AI in a human-centric intelligent society.
I have over 25 years of experience working in computer science and educated to Masters level. with a degree in Computer Science. Currently, I work for Fujitsu, as a Lead Deal Architect designing solutions for customers, working with Fujitsu Laboratories, to fulfil the Fujitsu vision of Human Centric Innovation. Our research focus is on creating cutting-edge solutions that benefit society, with particular emphasis on healthcare, manufacturing and finance. Our specialist research teams are actively engaged in Artificial Intelligence initiatives, as well as security technology research, and advanced cognitive networks research. Working with customers, collaboration partners and society as a whole to drive the evolution of ICT and help realize a safer and more prosperous world. Open Innovation is an essential element working with some of Europe’s highest profile initiatives, including the 5G Innovation Center - the world's first research center dedicated to 5G - and the European Union's largest ever research and innovation program, Horizon 2020.