Dr. Nuria Oliver
Nuria Oliver is Scientific Director at Telefonica R&D. She graduated top of her class and top of Spain in Telecommunications Engineering at the Universidad Politecnica of Madrid. She received a PhD from the Media Lab at MIT in 2000, after which she joined Microsoft Research as a researcher in Redmond, WA. In 2007, she returned to Europe to co-create the Research organization at Telefonica R&D, creating and leading her internationally recognized industrial research team in Barcelona. She is the first female Director at Telefonica R&D.
She has carried out foundational work in computational models of individual and aggregate human behavior using machine learning techniques, which has helped set the path for today’s intelligent systems. Her research has contributed to the development of intelligent multimodal interfaces, context-aware mobile computing applications, personalized services and Big Data for Social Good. Nuria has published over 200 scientific papers in international conferences, journals and book chapters with over 9600 citations and 40 filed/granted patents.
She has received awards, including MIT’s ‘TR100 Young Innovators Award’ (2004), a Rising Talent Award by the Women's Forum for the Economy and Society (2009) and several best scientific publication awards. She has been named a Senior Member of IEEE and the first Spanish female computer scientist named a Distinguished Scientist of the ACM.
As part of her service to the scientific community, she has had the co-chair role in 12 top-tier peer-reviewed ACM/IEEE/AAAI international conferences since 2009.
She regularly gives keynote talks about her research both scientific conferences, the general public and government bodies including the Spanish Senate, the ITU, European Commission, GSMA, OECD/PARIS21, United Nations and the Royal Statistical Society.
Her work has been featured over 100 times in newspapers, magazines, radio and TV, including authoring articles in TechCrunch, The Guardian and EL PAIS. Her article on the future of mobile phones is in the top 10 most read technology articles in EL PAIS in 2015. She was featured in Glamour magazine as 'one of the top female directors in Spain' (2015), in EL PAIS Sunday magazine as one of few 'female directors in technology' (2012), one of the ' 13 most influential young women in Spain’ (MujerHoy 2012), one of '100 leaders of the future’ (Capital Magazine 2009) and one of the 'Generation XXI: 40 Spanish youngsters that will make news in the Third Millenium ' (EL PAIS 2000).
From a societal perspective, her passion is to have positive impact in the world through her research, to make science and technology accessible to the general public and to inspire others (particularly young women) to pursue careers in science and technology. She devotes significant time to this purpose, and has given invited talks to large audiences – two TEDx talks and a WIRED talk —and to thousands of high schoolers. She has co-organized the first TEDxBarcelona event on emerging education with 1400+ participants, and the first Social Thinking course in Spain with ~200 participants.
Human Behavior Modeling from (Big) Data
6.7. 9:00–10:00, room D 239
We live in a world of data, of big data, a big part of which has been generated by humans through their interactions with both the physical and digital world. A key element in the exponential growth of human behavioral data is the mobile phone. There are more mobile phones in the world as humans. The mobile phone is the piece of technology with the highest levels of adoption in human history. We carry them with us all through the day (and night, in many cases), leaving digital traces of our physical interactions. Mobile phones have become sensors of human activity in the large scale and also the most personal devices. In my talk, I will present some of the work that we are doing at Telefonica Research in the area of modeling humans from a variety of human behavioral data, such as inferring personality, financial responsibility, attentiveness to messages or taste to provide recommendations. I will conclude by highlighting opportunities and challenges associated with building data-driven models of human behavior.