- GW Home
- Faculty and Staff
Speaker: J. Alan Roberson, Director of Federal Relations, American Water Works Association
This presentation will summarize the evolution of drinking water laws and regulation starting with the passage of the initial Safe Drinking Water Act (SDWA) in 1974 and subsequent amendments in 1986 and 1996. The Environmental Protection Agency (EPA) has published 18 major drinking water regulations between 1976 and 2006, and the evolution of these regulations will be discussed, how contaminants are selected for regulation and how the numerical standards are developed. The policy aspects of the regulatory development process will be discussed, along with how politics can shape drinking water regulations within the current statutory framework.
Time: Friday, November 4, 2011, 3:30 PM - 4:30 PM
Location: Duques Room 553 (2201 G Street, NW)
Speaker: Sharon Bertsch McGrayne
Sponsored by: The Departments of Physics, Statistics, The Institute for Integrating Statistics in Decision Sciences, and The Institute for Reliability and Risk Analysis of GWU.
From spam filters and machine translation to the drones over bin Laden's compound, Bayes' rule pervades modern life. Thomas Bayes and Pierre-Simon Laplace discovered the rule roughly 250 years ago but, for most of the 20th century, it was deeply controversial, almost taboo among academics. My talk will range over the history of Bayes' rule, highlighting Alan Turing who decrypted the German Enigma code and Jerome Cornfield of NIH and George Washington University who established smoking as a cause of lung cancer and high cholesterol as a cause of cardiovascular disease. The talk will be based on my recent book, The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines & Emerged Triumphant from Two Centuries of Controversy (Yale University Press).
Sharon Bertsch McGrayne is also the author of Nobel Prize Women in Science (National Academy Press), and Prometheans in the Lab (McGraw-Hill).
A former newspaper reporter and co-author of The Atom, Electricity & Magnetism (Encyclopaedia Britannica). She has been a panelist on NPR's Science Friday, and her work has been featured on Charley Rose. She has written for Scientific American, APS News, Science, Isis, the Times Higher Education Supplement, and other publications. Her books have been reviewed by Nature, Chemical & Engineering News, New Scientist, JAMA, Physics Today, Scientific American, Science Teacher, American Journal of Physics, Physics Teacher, Popular Mechanics, and others. Her webpage is at www.McGrayne.com.
Time: Friday, October 21, 2011, 4:00 PM
Location: Duques Room 651 (2201 G Street, NW)
Speaker: Sastry G. Pantula, Director of the Division of Mathematical Sciences at the National Science Foundation
Unit root tests in time series analysis have received considerable amount of attention since the seminal work of Dickey and Fuller (1976). In this talk, some of the existing unit root test criteria will be reviewed. Size, power and robustness to model misspecification of various unit root test criteria will be discussed. Unit root tests where the alternative hypothesis is a unit root process will be discussed. Tests for trend stationarity versus difference stationary models will be discussed briefly. Current work on unit root test criteria will also be discussed. Examples of unit root time series testing will be presented. Extensions to multivariate and heteroscedastic models will be discussed.
Sastry Pantula received his B.Stat and M.Stat from the Indian Statistical Institute, Kolkata and a Ph.D. In Statistics from Iowa State University. He has been a faculty member at North Carolina State University since 2002. He served as the Director of Graduate Programs from 1994-2002, and as the Department Head from 2002-2010. He is the 2010 ASA President. Currently, he is on loan to the National Science Foundation and serving as the Director of Division of Mathematical Sciences.
Time: Friday, September 30th 4:00-5:00 pm
Location: Duques 553 (2201 G Street, NW), Followed by Wine and Cheese Reception
Speaker: Ahmed A. Gomaa, Imedia Streams, LLC
ISocial media has increasingly been used by enterprises for reaching out to their customers for advertising campaigns, receiving product reviews, and users' preferences for new product development. This requires extraction and aggregation of information in the social media space for facilitating the decision making process. A key challenge is to automate this process of information discovery, extraction, and aggregation along relevant dimensions such as age, gender, location,interest, sentiment and authority. We have developed iPointTM, a system that enables the discovery, extraction and aggregation of social media, measuring the sentiments depicted online, providing an authority score for each author based on their interests along with the authors age, gender and location. We then use this information in conjunction with our ad server iServeTM. We use the derived intelligence from iPointTM as a daily updated internet panel that measures the internet waves to help distribute ads accordingly within advertising networks. Positive results are recorded by comparison to existing targeting technologies using both Yahoo! Right media exchange and Google content network. In this presentation we will focus on our authority ranking model which depends on Eigen Value calculations where we consider the number of posts by each author, the number of links and back comments on the posts, the relevancy of the post within each community and the amount of silent interaction with the posts. We present how we calculate the silent interactions in our model and how we use sparse matrix properties to optimize the calculation and storage time. The authority rank influences the general sentiment of a topic interest level, where sentiments from a highly ranked, more influential author have more weight than the sentiments of a less influential author, thus the community direction.
Time: Friday, September 16th 3:30-4:30 pm
Location: Duques 553 (2201 G Street, NW)
Speaker: Alp Muharremoglu, School of Business, UT Dallas
We consider a repeated newsvendor problem in which the decisionmaker (DM) does not have access to the underlying distribution of discrete demand. We analyze three informational settings: i.) the DM observes realized demand in each period; ii.) the DM only observes realized sales; and iii.) the DM observes realized sales but also a lost sales indicator that records whether demand was censored or not. We analyze the implications of censoring on performance and key characteristics that effective policies should possess. We provide a characterization of the best achievable performance in each of these cases, where we measure performance in terms of regret: the worst case difference between the cumulative costs of any policy and the optimal cumulative costs with knowledge of the demand distribution. In particular, we show that for both the first and the third settings, the best achievable performance is bounded (i.e., does not scale with the number of periods) while in the second setting, it grows logarithmically with the number of periods. We link the latter degradation in performance to the need for continuous exploration with sub-optimal decisions and provide a characterization of the frequency with which this should occur.
Time: Friday, October 14th 11:00-12:00 pm
Location: Duques 553 (2201 G Street, NW)