yt:channel:UC8LqgjK9f-iMHPN7rvBzVPA UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2013-06-04T15:36:48+00:00 yt:video:8h862Lz3kw4 8h862Lz3kw4 UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2017-05-05T18:55:55+00:00 2017-05-10T19:31:42+00:00 Suman Jana, Columbia University, Data Science Institute Colloquium Faculty Spotlight TITLE: Securing Software Systems: Beyond Whack-A-Mole ABSTRACT: Developing secure software is notoriously hard! Security vulnerabilities resulting from software bugs cost our economy billions of dollars every year. Unfortunately, the current ?whack-a-mole? approach to fixing bugs as they show up often break more things than they fix. In this talk, I will describe some of the fundamental challenges in software security and summarize the progress made towards solving them in the last decade. I'll also provide a broad overview of several principled approaches that software developers can follow to improve the robustness of software systems against malicious attackers. BIO: Suman Jana is an Assistant Professor in the Department of Computer Science at Columbia University. His primary research interests are in the areas of computer security and privacy. More specifically, he is interested in building automated tools for finding and fixing security and privacy vulnerabilities. He also occasionally delves into software engineering and operating systems. yt:video:MwI495Lvijg MwI495Lvijg UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2017-05-05T18:32:34+00:00 2017-05-08T07:51:26+00:00 Dr. Michael Winter, Columbia University, Data Science Institute Colloquium SPEAKER: Dr. Michael Winter, Senior Fellow, Advanced Technology Pratt & Whitney, United Technologies Corporation TITLE: Systems Engineering: Imperatives, Definitions, Technology & Talent ABSTRACT: The lecture will present the motivation, mechanics, and methodologies of model-based systems engineering as applied to product platforms and infrastructures that are often safety or operationally critical. Cyber-physical system-of-systems that combine both physics and controls form the basis of modern society. Application of systems engineering principles in an analytic context with focus on requirements, architecture, model-based development, and design flows will be presented as applied in an industrial context. DATE: April 26th, 2017 yt:video:H_7MnkJXEqM H_7MnkJXEqM UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2017-05-05T18:04:10+00:00 2017-05-05T20:40:36+00:00 Air Force Lt. Gen. William Bender, Columbia University, Data Science Institute Colloquium Series TITLE: Online at the Front Line: Air Force Cybersecurity and the Challenge of Winning Wars in the Digital Age SPEAKER: Air Force Lt. Gen. William J. "Bill" Bender, Chief, Information Dominance and Chief Information Officer Office of the Secretary of the Air Force ABSTRACT: The U.S. Air Force was the world?s dominant air force in the industrial age ? is it prepared to win in the digital era? Lt. Gen. Bill Bender, the Air Force?s Chief Information Officer and a veteran pilot of nearly a dozen military aircraft, is quick to note that there is no ?divide? between the digital world and its tangible counterpart: every modern Air Force mission is conducted in, through and from the cyber realm. Every industry in the world faces similar challenges with digital technology, data and cybersecurity, but perhaps few with more at stake than our nation?s armed forces. Gen. Bender will discuss the challenges of management and innovation in a vast IT enterprise, efforts to improve how the Air Force acquires and develops technology and recruits digital experts, and the best way ahead to guarantee American cybersecurity in a rapidly-changing world. DATE: March 8th, 2017 yt:video:kXHfQ1KafK4 kXHfQ1KafK4 UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2017-02-24T16:44:29+00:00 2017-07-16T20:23:27+00:00 Movie Stored and Retrieved from DNA Molecules A copy of this 1895 French film, “Arrival of a train at La Ciotat,” was encoded into synthetic DNA molecules and later retrieved using a new coding strategy developed by Yaniv Erlich and Dina Zielinski at Columbia University and New York Genome Center. yt:video:l2mGmMni63Q l2mGmMni63Q UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2016-09-21T15:04:21+00:00 2016-09-21T15:04:21+00:00 Susan Athey, Data Science Colloquium Series Susan Athey, The Economics of Technology Professor | Stanford University Title: Adapting machine learning methods for causal inference: applications to evaluating large scale experiments ABSTRACT: This talk will review several recent papers which aim to modify popular machine learning methods for problems of causal inference, such as evaluating the impact of a treatment using experimental or observational data. We will focus on estimation of treatment effect heterogeneity (that is, which individuals are predicted, based on their features, to have higher or lower benefits of a treatment) in settings such as A/B testing platforms or medical trials where it is important to provide confidence intervals in addition to estimated effects. We analyze the tradeoffs between evaluating model fit based on observed outcomes, and evaluating model fit based on an estimate of the (unobserved) treatment effect. We build on this work to show how random forests can be modified to provide asymptotically centered estimates of treatment effect heterogeneity in experiments or observational studies. yt:video:9KdZxwQgaTo 9KdZxwQgaTo UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2016-09-21T15:01:10+00:00 2016-11-24T02:32:46+00:00 Darrell Duffie, Data Science Institute Colloquium Series Darrell Duffie, Dean Witter Distinguished Professor of Finance | Stanford University Title: The Importance of Reforming LIBOR and Other Benchmarks ABSTRACT: Reliable benchmarks serve several important economic functions. The price transparency afforded by a good benchmark improves the ability of market participants to conduct comparison shopping. Second, benchmarks allow the customers of financial services firms to more easily monitor their delegated execution costs. Finally, benchmarks serve as settlement devices for related markets. Relying on a reference rate such as LIBOR, banks and derivatives exchanges can provide their clients with a rich set of floating-rate products, such as mortgages, corporate loans, swaps, forwards, swaptions, caps, floors. I will describe the current situation in the reform of interest rate benchmarks, especially LIBOR, focusing on improvements in the LIBOR fixing method and the substitution of alternative reference rates for LIBOR in the interest rate derivatives market. The main concern here is the extremely heavy volume of swaps referencing LIBOR, relative to the volume of short term bank borrowing transactions that can be used to fix LIBOR. yt:video:W0gwrCIXx40 W0gwrCIXx40 UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2016-08-11T14:24:36+00:00 2017-04-10T12:36:11+00:00 Firing Neurons in Mouse Visual Cortex In the above video, neurons repeatedly stimulated with light are trained to work together. They can be reactivated as a group if just one neuron is stimulated as much as a day later. The experiments are detailed in a new study in the journal Science. (Courtesy of Rafael Yuste Laboratory/Columbia University) yt:video:sF2JZNKlfYY sF2JZNKlfYY UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2016-06-16T19:40:02+00:00 2016-09-22T19:23:00+00:00 Data Science Student Challenge (2015) Columbia Data Science Society, the Data Science Institute and Microsoft take students from across multiple disciplines and use a hackathon format to introduce them to the Data Science discipline. yt:video:DcPrOjJ_HeQ DcPrOjJ_HeQ UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2016-06-09T15:29:26+00:00 2016-06-09T16:00:34+00:00 Speed-Networking Seminar | Bob Carpenter : Stan: Bayesian Inference Made Easy Bob Carpenter, Research Scientist at Columbia University, Department of Statistics yt:video:RM9Q1zbXuLs RM9Q1zbXuLs UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2016-06-09T15:28:23+00:00 2016-06-09T15:37:12+00:00 Speed-Networking Seminar | John Paisley: Scalable, Structured Models for Text Description yt:video:P2fGKYSmPgw P2fGKYSmPgw UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2016-06-09T15:27:37+00:00 2016-06-09T16:27:42+00:00 Speed-Networking Seminar | Yash Kanoria: Exploration vs Exploitation in Two-sided Markets Yash Kanoria, Assistant Professor in the Decision, Risk and Operations at Columbia Business School yt:video:rbfs_xJhLIM rbfs_xJhLIM UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2016-06-09T15:27:34+00:00 2016-06-09T15:47:37+00:00 Speed-Networking Seminar | Michael Burke : Automated, High-Throughput Experiments Michael Burke, Assistant Professor in Mechanical Engineering at Columbia University yt:video:6rsYiyWih0g 6rsYiyWih0g UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2016-06-08T20:38:52+00:00 2016-06-10T14:08:16+00:00 Data Visualization | Nicholas Tatonetti: Assistant Professor of Biomedical Informatics Lightning Talk: Nicholas Tatonetti, Assistant Professor of Biomedical Informatics yt:video:EqHPQEr2H8o EqHPQEr2H8o UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2016-06-08T20:38:31+00:00 2016-06-09T16:26:20+00:00 Data Visualization | Mark Hansen, David and Helen Gurley Brown Professor of Journalism & Innovation Lightning Talk: Mark Hansen, David and Helen Gurley Brown Professor of Journalism and Innovation yt:video:sVuq0iDGFrc sVuq0iDGFrc UC8LqgjK9f-iMHPN7rvBzVPA Columbia Data Science https://www.youtube.com/channel/UC8LqgjK9f-iMHPN7rvBzVPA 2016-06-08T20:37:49+00:00 2016-06-09T16:24:11+00:00 Data Visualization | Laura Kurgan, Associate Professor of Architecture, Planning and Preservation Laura Kurgan Associate Professor of Architecture, Planning and Preservation