NY Data Science Seminar Series Presents: Jeannette M. Wing | Data for Good

Tuesday, February 20, 2018 - 5:30pm to 7:30pm
Bloomberg Center, Cornell Tech
2 West Loop Road
New York, NY 10044
United States

Jeannette M. Wing
Avanessians Director of the Data Science Institute Professor of Computer Science Columbia University
Data for Good

Reception: 5:30pm-6:30pm

Talk: 6:30pm-7:30pm

LOCATION
Bloomberg Center, Cornell Tech
2 West Loop Road
New York, NY 10044

Every field has data. We use data to discover new knowledge, to interpret the world, to make decisions, and even to predict the future. The recent convergence of big data, cloud computing, and novel machine learning algorithms and statistical methods is causing an explosive interest in data science and its applicability to all fields. This convergence has already enabled the automation of some tasks that better human performance. The novel capabilities we derive from data science will drive our cars, treat disease, and keep us safe. At the same time, such capabilities risk leading to biased, inappropriate, or unintended action. The design of data science solutions requires both excellence in the fundamentals of the field and expertise to develop applications which meet human challenges without creating even greater risk.

The Data Science Institute at Columbia University promotes “Data for Good”: using data to address societal challenges and bringing humanistic perspectives as—not after—new science and technology is invented. Started in 2012, the Institute is now a university-level institute representing over 250 affiliated faculty from 12 different schools across campus. Data science literally touches every corner of the university.

In this talk, I will present the vision on how the Institute plans to address some of the key challenges and opportunities of data science, highlighting educational and research activities, as well as future initiatives that may directly impact the data science community at Columbia, New York City, and beyond.

About the Speaker

Jeannette M. Wing is the Avanessians Director of the Data Science Institute at Columbia University. Jeannette comes to Columbia from Microsoft, where for the past four years she has been Corporate Vice President of Microsoft Research, overseeing a global network of research labs. She is widely recognized for her intellectual leadership in computer science, and is now helping to define the new, emerging field of data science. Jeannette’s seminal essay, titled “Computational Thinking,” was published more than a decade ago and is credited with helping to establish the centrality of computer science to problem-solving in fields where previously it had not been embraced.

Before joining Microsoft in 2013, Jeannette held positions at Carnegie Mellon University and the National Science Foundation. She served Carnegie Mellon as Head of the Computer Science Department twice and Associate Dean for Academic Affairs. At the National Science Foundation, she was Assistant Director of the Computer and Information Science and Engineering Directorate, where she oversaw the federal government’s funding of academic computer science research. Her areas of research expertise include security and privacy, formal methods, programming languages, and distributed and concurrent systems. Jeannette has been recognized with distinguished service awards from the Computing Research Association and the Association for Computing Machinery. She holds bachelor’s, master’s, and doctoral degrees from MIT.

This event is part of the NYC Data Science Seminar Series, organized by Microsoft Research NYC, Facebook, NYU Center for Data Science, Columbia University, and Cornell Tech.

Speaker(s): 

Jeannette Wing

Jeannette Wing
Columbia University
Data Science Institute
Avanessians Director
Computer Science
Professor

Jeannette comes to Columbia from Microsoft, where from 2013 to 2017 she served as Corporate Vice President of Microsoft Research, overseeing a global network of research labs. She is widely recognized for her intellectual leadership, having earned the respect and admiration of colleagues across the field for her role in the dramatic transformation of data science into a discipline essential to so much scholarly discovery and productive invention.

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