Below is a talk that many of you may find relevant.
Begin forwarded message:
From: "Robin E. Brooks" <rebrooks@uw.edu> Subject: [Dataseminar] Data Science Seminar: Uyi Stewart, May 23, 3:30 p.m., PAA A102 Date: May 14, 2018 at 11:14:41 PDT To: dataseminar@u.washington.edu, escience_allhands <escience_allhands@uw.edu>, "escience_bbl@u.washington.edu" <escience_bbl@u.washington.edu>, escience_affiliates@uw.edu, iths_tnt@uw.edu
Hello everyone,
We hope you can join us for our next Data Science Seminar <http://escience.washington.edu/uw-data-science-seminar/Stewart> featuring Uyi Stewart <https://www.itu.int/en/ITU-T/AI/Pages/stewart.aspx>, director of Global Development Strategy, Data and Analytics at the Bill and Melinda Gates Foundation. The seminar will be on Wednesday, May 23, at 3:30 p.m. in the Physics/Astronomy Auditorium, room A102. Refreshments will be served and all are welcome to attend.
Please feel free to post the attached flier and forward to those interested! This seminar is co-sponsored by Urbanlytics <http://urbanalytics.uw.edu/>.
Data science, AI, and big data analytics for global good & social impact
Abstract:
Over the past decade, we have witnessed an unprecedented explosion in data and in the way that analytics is being used to generate insights from such data. For example, in agriculture we used to rely mainly on subjective interpretation of weather or the farmer’s almanac to support farmer’s productivity. Now, we rely on remote sensing and predictive analytics to forecast yield, crop health, when or what to plant, etc. In healthcare, our polio eradication campaigns used to be targeted uniformly across geographies causing supply chain and coverage estimation nightmares. Now, we rely on analytics to help predict and smartly focus our interventions. This transition from diagnostic to predictive problem solving is happening across research, academic, commercial and non-governmental global development efforts, albeit with different incentives and underlying assumptions about the Data Value Chain (DVC).
I’ll describe my journey from a commercial global innovation lab to the Bill & Melinda Gates Foundation, starting with our work in Africa (Nairobi, Kenya) to set up the first commercial research lab on the continent that is focused on applied and far-reaching exploratory research. I will describe how data and its usage have emerged as one of the most important global public goods at Gates Foundation; in particular, how we are using innovative technologies across the DVC to shape/influence our program strategy teams and the engagement with our partners in pursuit of our core belief that all lives have equal value. In light of these, I will motivate a unifying DVC and global data architecture that will enable data scientists and others from the research, academic, and commercial communities to contribute toward global public good (data science for social good) and help to make tomorrow better than today for billions of people.
Bio:
Dr. Uyi Stewart's team is responsible for applying innovative technologies such as machine learning, artificial intelligence, etc. to optimize the use of data for decision-making and for delivery effectiveness, as well as leveraging the foundation’s data investments to create global public goods. Prior to joining the Gates foundation in March 2017, Uyi previously spent 13 years with IBM Research where he was promoted to distinguished engineer (one of the firm’s highest technical honors) in 2014, and he was also the co-founder and chief scientist of IBM Research – Africa from 2012 – 2016 (the first lab on the continent for conducting applied and far-reaching exploratory research into Africa’s grand challenges).
Kind regards,
Robin Brooks Communications Associate | eScience Institute <http://escience.washington.edu/> 206.543.9674 & rebrooks@uw.edu <mailto:rebrooks@uw.edu> Follow us on Twitter <https://twitter.com/uwescience>, Facebook <https://www.facebook.com/uwescienceinstitute/> and YouTube <https://www.youtube.com/channel/UCLKSeDZWDqBzKRfHTabg1lQ>! University of Washington 3910 15th Ave NE, Campus Box 351570 | Seattle, WA 98195 _______________________________________________ Dataseminar mailing list Dataseminar@u.washington.edu http://mailman11.u.washington.edu/mailman/listinfo/dataseminar