The Next Generation of Search Engines https://cyber.law.harvard.edu/events/luncheon/2015/09/Rudin *with Cynthia Rudin, Associate Professor of Statistics at MIT* Today, 6.00 pm Webcast live:http://cyber.law.harvard.edu/interactive/webcast http://nexa.polito.it/berkman-webcast-live <http://nexa.polito.it/berkman-webcast-live> *From Cynthia* Hi Everyone! My goal for this year is to anticipate the next generation of search engines. I say that the current generation of search engines just tells you where to find information (returns a list of webpages), where the next generation of search engines find the information for you (reads the webpages and returns content!). I would like to cordially invite you to a brainstorming session on what the next generation of search engines might look like. Challenges for the audience: * What are some cases where Google fails miserably? * Do you sometimes want to find the answer to a complicated type of question? How do you envision the answer being presented? * Do you have ideas of what the capabilities will be for the next generation of search engines? * What are some lessons we can learn from search engines from the past? This will be mainly audience participation. Audience members are invited to *bring one slide*. Please send it in advance to rudin@mit.edu. As an introduction to this topic, I will describe "Growing A List" which is a search engine for the problem of "set expansion." See you there! About Cynthia Cynthia Rudin is an associate professor of statistics at the Massachusetts Institute of Technology associated with the Computer Science and Artificial Intelligence Laboratory and the Sloan School of Management, and directs the Prediction Analysis Lab. Her interests are in machine learning, data mining, applied statistics, and knowledge discovery (Big Data). Her application areas are in energy grid reliability, healthcare, and computational criminology. Previously, Prof. Rudin was an associate research scientist at the Center for Computational Learning Systems at Columbia University, and prior to that, an NSF postdoctoral research fellow at NYU. She holds an undergraduate degree from the University at Buffalo where she received the College of Arts and Sciences Outstanding Senior Award in Sciences and Mathematics, and three separate outstanding senior awards from the departments of physics, music, and mathematics. She received a PhD in applied and computational mathematics from Princeton University. She is the recipient of the 2013 INFORMS Innovative Applications in Analytics Award, an NSF CAREER award, and was named as one of the "Top 40 Under 40" by Poets and Quants in 2015. Her work has been featured in Businessweek, The Wall Street Journal, the New York Times, the Boston Globe, the Times of London, Fox News (Fox & Friends), the Toronto Star, WIRED Science, U.S. News and World Report, Slashdot, CIO magazine, Boston Public Radio, and on the cover of IEEE Computer. She is presently the chair-elect for the INFORMS Data Mining Section, and currently serves on committees for DARPA, the National Academy of Sciences, the US Department of Justice, and the American Statistical Association.
