DSI Collaborates with Columbia's Global Center in Brazil
Jeanette M. Wing, Avanessians Director of the Data Science Institute (DSI) at Columbia University, gave a lecture titled “Using Data for Good” at Columbia’s Global Center in Rio de Janeiro, Brazil. The lecture took place at the Engineering School of the Federal University of Rio de Janeiro.
In her talk, Wing discussed “Data for Good,” the institute's tagline that emphasizes the need to tackle societal problems and promote the fair and ethical use of data. Now more than ever, said Wing, those involved in the creation of technology “must take into consideration the legal, social, cultural, and philosophical questions as we invent new technology - not after it is being used.” During her talk, Wing presented the vision and part of the research being developed at the Institute that embody “Data for Good.”
Columbia Global Center in Rio de Janeiro is a hub for Columbia programs and initiatives relevant to Brazil. Established in 2013, the Center contributes to Brazil's academic and research environment, while also allowing members of the Columbia community to increase their knowledge and explore academic opportunities within Brazil.
“We were delighted to welcome Jeannette Wing to Brazil for an exciting program of visits and lectures,” said Thomas Trebat, Director of the Columbia Global Center in Rio de Janeiro. “Data for good is a concept that resonates throughout the world, including here in Brazil, and Jeannette’s global reputation and the global importance of data science to the future of Brazil created a marvelous opportunity for the Global Center to extend Columbia’s brand and to create new and mutually beneficial partnerships.”
Columbia Global Centers | Beijing
Tian Zheng, associate director for education at the Data Science Institute and professor of statistics at Columbia, also delivered a lecture, Statistical Thinking: Injecting Wisdom into Big Data Applications, that was hosted recently by Columbia Global Centers | Beijing. Her lecture detailed the growing use of statistics and big data in various fields of research and the challenges researchers face in making sure their data is impartial and their algorithms unbiased. Statistics provides the formal mathematical language for data-driven inference, modeling and prediction with a focus on measurements, variation and uncertainty. It is an essential part of any data science application.
--By Robert Florida