Tag Archives: Data Science

AI, Society and Organizations

On the 7th of March 2019, CNETS Professor Luis Rocha will participate in a panel organized by Nova SBE’s Executive Education, Instituto Gulbenkian da Ciência and ISI Foundation with the theme of AI, society and organisations: experiences from applied projects in governments, companies and NGO’s, where the role of data science in today’s world will be discussed.

Other guest speakers, include Rayid Ghani, director of the Center for Data Science and Public Policy in the University of Chicago, founder of the Data Science for Social Good fellowship and Chief Scientist at the Obama for America 2012, Daniela Paolotti, Ciro Cattuto, Joana Gonçalves-Sá and Leid Zejnilovic.

Charting interdisciplinary research opportunities between data and life sciences

CNetS Professor Luis Rocha, together with ISI foundation (ISI) scientist Ciro Cattuto organize a workshop with the Instituto Gulbenkian de Ciencia to explore synergies between data/computational science and the life, health and social sciences. More information on the workshop event page.

Continue reading Charting interdisciplinary research opportunities between data and life sciences

Team led by Luis Rocha awarded NIH grant to improve chronic-disease management with Data and Network Science

Luis M. RochaThe National Institutes of Health, under the National Library of Medicine’s program on data science research, awarded a $1.55 million grant to an interdisciplinary team lead by Luis Rocha, a professor of informatics, member of CNETS and the director of the NSF-NRT complex networks & systems program at the School of Informatics, Computing, and Engineering. The four-year project, a collaboration between SICE and the Indiana University School of Nursing, will employ innovative data- and network-science methods to produce myAURA, an easy-to-use web service for epilepsy patients. myAURA will be based on a large-scale epilepsy knowledge graph built by integrating data from social media, electronic health records, patient discussion boards, scientific literature databases, advocacy websites, and mobile app data. The knowledge graph will, in turn, be used to fuel recommendation and visualization algorithms based on the automatic inference of relevant associations. The inference will follow algorithms developed by Rocha’s team to remove redundancy and extract factual information from large knowledge graphs as well as parsimonious network visualizations developed by Katy Börner, Distinguished Professor of Engineering & Information Science at SICE.  Continue reading Team led by Luis Rocha awarded NIH grant to improve chronic-disease management with Data and Network Science