Keynote Speakers

Elizabeth Churchill (Director of User Experience at Google)

Elizabeth Churchill is a Director of User Experience at Google, the Executive Vice President of the Association of Computing Machinery, a member of the ACM's CHI Academy, and an ACM Distinguished Scientist and Distinguished Speaker. With a background in psychology (neuro, experimental, cognitive and social), Artificial Intelligence and Cognitive Science, for the past 20 years she has drawn on social, computer, engineering and data sciences to create innovative end-user applications and services. She has built research teams at Google, eBay, Yahoo, PARC and FujiXerox. She holds a PhD from the University of Cambridge, an honorary Doctor of Science (DSc.) from the University of Sussex, and in September will be awarded an honorary doctorate from the University of Stockholm. In 2016 she received a Citris-Banatao Institute Award Athena Award for Women in Technology for her Executive Leadership.

Grega Milcinski (CEO, Sinergise)

Born in 1980 in Slovenia, he studied Physics and co-founded Cosylab inc. at age 21, a company developing control systems for particle accelerators and large experiments in physics. In 2008 Grega moved to become CEO and co-founder of Sinergise, specialising in software for advanced geospatial applications, helping Europe to efficiently manage and control agriculture policy and introducing land administration systems to developing countries in Africa. With his colleagues they have recognised the potential of open Copernicus earth observation data early but soon hit a wall trying to use existing technologies to work with these large datasets. Deciding to do something about it, Sentinel Hub was born. A Copernicus Masters award winning service for processing and distribution of satellite data is exploiting AWS Public Datasets to provide seamless access to the data to more than 10.000 registered users, mostly web developers creating applications on top of remote sensing data. After working with governmental clients in Balkan, Western Europe, Asia and Africa, Grega is now engulfed in building a global Internet business, which is nowadays processing two million requests every day.

Detlef D Nauck (Chief Research Scientist for Data Science at BT Technology)

Dr Detlef Nauck is a Chief Research Scientist for Data Science with BT's Research and Innovation Division located at Adastral Park. Detlef has 30 years of experience in data analytics, machine learning, and AI. At BT, he is leading a group of international research scientists working on improving the use of Data Science. Detlef focuses on establishing best practices in Data Science for conducting analytics professionally and responsibly leading to new ways of analysing data for making better decisions. Part of his role is leading the initiative on the development and use of responsible and ethical AI in the company. Detlef is a computer scientist by training, a Visiting Professor at Bournemouth University and has published 3 books, over 120 papers, holds 10 patents and has 30 active patent applications.

Keynote Title: Test Driven Machine Learning and Model Factories

Abstract: Data Scientists and machine learning specialists are familiar with testing principles during the model building phase like cross-validation, but they are often unfamiliar with test-driven software engineering principles. While testing a learned model gives an idea how well it might perform on unseen data this is not sufficient for model deployment. Trying to learn from test driven software development practices we look across the machine learning life cycle to understand where we need to test and how this can be done. The testing of data, for example, is essential as it not only drives the machine learning phase itself, but it is paramount for producing reliable predictions after deployment. Testing the decisions made by a deployed machine learning model is equally important to understand if it delivers the expected business value. To operate test-driven machine learning in production we look at the concept of model factories. They add an orchestration layer that automates as much of the testing and model building as possible and supports governance.

Giulio Sandini (Director of Research - Italian Institute of Technology)

Giulio Sandini is Director of Research at the Italian Institute of Technology and full professor of bioengineering at the University of Genoa. He was research fellow and assistant professor at the Scuola Normale Superiore in Pisa and Visiting Research Associate at the Department of Neurology of the Harvard Medical School. In 1990 he founded the LIRA-Lab (Laboratory for Integrated Advanced Robotics, and in 1996 he was Visiting Scientist at the Artificial Intelligence Lab of MIT. Since 1980 Giulio Sandini coordinated several international projects in the area of computer vision, cognitive sciences and robotics. Among them the project RobotCub, funded by the "Cognitive Systems" unit of the European Union from 2004 to 2010, where he coordinated the activities of 11 European partners contributing to the realization of the iCub humanoid platform as a tool to investigate human sensory, motor and cognitive development. (FP6-P004370:

Keynote Title: Embodied Intelligence: from Robot Actions to Mutual Understanding

Abstract: Robotic technologies have been steadily improving in the last years up to a point that sensing and motion abilities of robots are approaching and in some cases exceeding those of humans. These abilities, spanning from robots able to express emotions to robots executing fantastic gymnastic exercises have created the impression that a society where humans and robots co-exist and collaborate is not very far away. Is this true?
During the talk I will argue that even if robots are motorically and sensorially very skilled and extremely clever in action execution, the technologies supporting their interaction with humans are still very primitive and based mainly on human ability to adapt to the technology rather than on mutual understanding. Stemming from this observation I will address three points: first the fact that the asymmetry between action execution and understanding is rooted in our limited knowledge of the mechanisms at the basis of human social interaction. Second that discovering the principles of mutual understanding is a necessary intermediate step to investigate alternative “artificial” technologies implementing such principles (airplanes do not flap wings but bird’s wings and airplane’s propellers are two different technologies acting on the same principles). Finally I will argue that robotics can serve a very crucial role by joining forces with the communities studying embodied intelligence and the cognitive aspects of social interaction and by co-designing robots able to establish a mutual communication channel with a human partner (the distinctive mark of human social interaction) [Sandini & Sciutti, 2018].

Iain Brown (Head of Data Science for SAS UK&I)

Dr. Iain Brown is the Head of Data Science for SAS UK&I and Adjunct Professor of Marketing Analytics at University of Southampton. Over the past decade he has worked across a number of sectors, providing thought leadership on the topics of Risk, AI and Machine Learning and their ethical applications. During his time at SAS he has been involved in delivering numerous projects and driving innovation in the fields of AI and the corresponding fields of machine learning, deep learning and natural language understanding. As an experienced public speaker and published author he has presented at a number of internationally renowned conferences and conventions and has papers published in the European Journal of Operational Research, International Journal of Forecasting and the Journal of Expert Systems with Applications on the aforementioned areas of expertise.

Keynote Title: AI for the good of humanity

Abstract: There is too often a focus on the negative implications of AI and the fear of its unethical usage. What is often overlooked is its potential to be a transformative power for good, and it’s ability to enhance and empower society as a whole. This presentation details real-world applications of how AI is being deployed to solve humanitarian issues around poverty, health and human rights.