Computing Community Consortium Blog

The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.

NSF Data Science Seminar- Computational Thinking, Inferential Thinking and Data Science

January 27th, 2016 / in Announcements, NSF, research horizons / by Helen Wright

jordan_smallThe AAAS Science and Technology Policy Fellows at the National Science Foundation (NSF) have organized another talk in their Data Science Seminar Series from Michael I. Jordan on Computational Thinking, Inferential Thinking and Data ScienceThe talk will be on Thursday, January 28 from 11:00-12:00PM at NSF Stafford I, Room 110. 

Michael I. Jordan is the Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley. His research interests bridge the computational, statistical, cognitive and biological sciences, and have focused in recent years on Bayesian nonparametric analysis, probabilistic graphical models, spectral methods, kernel machines and applications to problems in distributed computing systems, natural language processing, signal processing and statistical genetics.


The phenomenon of Big Data is creating a need for research perspectives that blend computational thinking (with its focus on, e.g., abstractions, algorithms and scalability) with inferential thinking (with its focus on, e.g., underlying populations, sampling patterns, error bars and predictions). There are many grand challenges involving in creating such a blend; indeed, there are foundational problems that span computation and inference that are far from being solved. There are also many implications for research, technology, policy and education.

No RSVP is required if you are coming in person. If you are interested in attending but can’t come in person, the talk will be webcast here. Please register for the webcast beforehand. 

NSF Data Science Seminar- Computational Thinking, Inferential Thinking and Data Science