Past Events

Alma Mater

Friday, February 16, 2018 - 12:00pm to 1:30pm
Schapiro Hall (CEPSR) Davis Auditorium
Columbia University
New York, NY 10027
United States

Sharyn O’Halloran, George Blumenthal Professor of Political Economics and Professor of International and Public Affairs at Columbia

Friday, February 9, 2018 - 12:30pm to 1:30pm
United States

Jeannette Wing, Avanessians Director of the Data Sciences Institute at Columbia University

"FATES: Fairness, Accountability, Transparency, Ethics, Safety and Security"

Wednesday, January 31, 2018 - 4:30pm to 6:00pm
New York, NY 10027
United States

Columbia Data Science Institute Industry Innovation Seminars


Presented by Neal Goldstein, Managing Director JP Morgan – Global Head of Connectivity Solutions

Friday, December 8, 2017 - 7:00pm to 8:00pm
United States

A panel discussion on Net Neutrality to discuss the Federal Communications Commission's expected December 14th vote.

Friday, December 8, 2017 - 9:00am to 1:00pm
United States

The conference on Ten Years After the Financial Crisis will bring together leading experts in law, economics and public policy from academia, government and business, to examine the implications of the financial crisis on the politica

Tuesday, December 5, 2017 - 5:00pm to 6:00pm
Schapiro Hall (CEPSR) Davis Auditorium
Columbia University
New York, NY 10027
United States

Dan Jurafsky | Stanford University, Linguistics and Computer Science

Thursday, November 30, 2017 - 11:00am to 12:00pm
New York, NY 10027
United States

Columbia Data Science Institute Industry Innovation Seminars


Presented by Lucas Saloumi (Data Scientist), Rick Winslow (Head of Commercial Digital Innovation) and Zeina Zeitouni (Product Manager)

Capital One is a pioneer in applying both artificial intelligence and design thinking to make banking smarter, more intuitive and personal. Presenters from the Commercial Banking Digital Innovation team will show how designers and data scientists can work together on cross-functional teams to solve complex problems and build compelling new products. They will share examples of how machine learning classification and outlier detection has been applied in their business. And they will discuss the challenges faced when deploying intelligent systems at scale, all while keeping customers and business partners engaged in the process.

Monday, November 20, 2017 - 11:30am to 12:30pm
New York, NY 10027
United States

This is event is co-sponsored by the Department of Computer Science's Distinguished Lecture Series.

Yann LeCun, Facebook AI Research & New York University

Wednesday, November 15, 2017 - 6:00pm to 7:30pm
New York, NY 10027
United States

Dr. Geoffrey West
Author of Scale: The Universal Laws of Growth, Innovation, Sustainability and the Pace of Life in Organisms, Cities, Economies, and Companies

Friday, November 3, 2017 - 11:00am to 12:00pm
Columbia University
New York, NY 10027
United States

Data Science Institute | Sense, Collect & Move Data Center Seminar

Speaker: Steven Low, Caltech

Optimal power flow (OPF) is fundamental because it underlies numerous power system operation and planning problems. In this talk, I will give a sample of optimization problems in the management of a large network of distributed energy resources. The nonlinearity of power flow equations leads to the nonconvexity of OPF, one of the main computational challenges in power system applications. We describe a method to deal with nonconvexity through semidefinite relaxation. Semidefinite programs are hard to scale to large OPF problems. We describe a highly scalable distributed solution based on ADMM. These algorithms are offline in that they iterate until the computation has converged before applying the final solution to the grid, and are therefore not suitable for real-time optimization of distributed energy resources at scale. We describe realtime OPF that explicitly exploits the network as a power flow equation solver and characterize its performance in tracking changing network conditions. Finally, in practice, not all network nodes have sensors or can be controlled. We characterize controllability and observability of power flow dynamics in terms of the spectral properties of its Laplacian matrix. This characterization can be used to optimize the placement of sensors and actuators in the grid.

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