Series
ISyE Distinguished Lecture Series

Series Type
Event Series
Description
Associated Organization(s)
Associated Organization(s)

Publication Search Results

Now showing 1 - 7 of 7
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    Riding Technology Waves: Opportunities for Operations Research
    (Georgia Institute of Technology, 2017-03-30) Dietrich, Brenda
    Brenda Dietrich's talk includes a fly-by of five decades of information technology beginning with its use to automate business processes and extending to its current role in intermediating social processes. The resulting "data exhaust," together with the availability of low cost computing capacity, spawned the age of analytics, the rise of big data, and the birth of cognitive computing. The past, current, and potential role of operations research in these technology waves will be discussed.
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    Adventures in Policy Modeling!
    ( 2016-03-28) Kaplan, Edward H.
    Policy Modeling refers to the application of operations research, statistics, and other quantitative methods to model policy problems. Recognizing that analyses of all sorts often exhibit diminishing returns in insight to effort, the hope is to capture key features of various policy issues with relatively simple “first-strike” models. Problem selection and formulation thus compete with the mathematics of solution methods in determining successful applications: where do good problems come from? how can analysts tell if a particular issue is worth pursuing? In addressing these questions, I will review some personal adventures in policy modeling selected from public housing, HIV/AIDS prevention, bioterror preparedness, suicide bombings and counterterrorism, in vitro fertilization, predicting presidential elections, and sports.
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    Lessons Learned on Hard Work, Thinking Ahead, and Just Showing Up
    ( 2014-10-09) Marshall, John
    There is no such thing as an overnight success. Like the actor who does ten years of dinner theater before making it big, most of today’s leaders undergo significant challenges on the road to success. However, applying those insights can lead to significant growth. Join John Marshall, Senior Vice President and General Manager of AirWatch by VMware, as he shares how his experiences at Georgia Tech helped him take AirWatch from an apartment startup to a billion dollar buyout.
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    Service Engineering: Data-Based Science in Support of Service Management, or Empirical Adventures in Call Centers and Hospitals
    (Georgia Institute of Technology, 2011-02-24) Mandelbaum, Avishai
    Synopsis: In this lecture, Dr. Mandelbaum will describe examples of complex service operations for which data-based simple models have been found useful, which he refers to as "Simple Models at the Service of Complex Realities." Examples include call centers, hospitals, banks, courts and more. He views these service systems through the mathematical lenses of Queueing Science, with a bias towards Statistics. The mathematical framework for his models is asymptotic queueing theory, where limits are taken as the number of servers increases indefinitely, in ways that maintain a sought-after (often delicate) balance between staffing level and offered-load. A specific such balance reveals an operational regime that achieves, under already moderate scale, remarkably high levels of both service quality and efficiency. This is the QED regime (Quality- & Efficiency- Driven), discovered by Erlang and substantiated mathematically by Halfin & Whitt. The data-source for the lecture is a unique data repository from call centers and hospitals. The data is maintained at the Technion's SEE Laboratory (Service Enterprise Engineering). It is unique in that it is transaction-based; it details the individual operational history of all the service transactions (e.g., calls in a call center or patients in an emergency department). One source of data, publicly available, is a network of four call centers of a U.S. bank, spanning two and a half years and covering about 1,000 agents; there are 218,047,488 telephone calls overall, out of which 41,646,142 were served by agents, while the rest were handled by answering machines. The data can be explored via SEEStat, an environment for online Exploratory Data Analysis. SEEStat is accessible here after registration.
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    Learning From the Experiences of Others
    (Georgia Institute of Technology, 2010-09-23) Efron, Bradley
    Familiar statistical estimates such as batting averages, political polls, and medical trial results are obtained by direct observation of cases of interest. Sometimes, though, we can learn from the experience of "others": for instance there may be information about Player A's batting ability in the observed averages of Players B,C,D, etc. In his presentation, Professor Efron will present several examples showing how this works in practice, indicating some of the surprising theoretical ideas involved. The talk is mainly descriptive in nature, and is intended for a general scientific audience.
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    Operations Research and Homeland Security: From Models to Implementation
    (Georgia Institute of Technology, 2009-03-05) Wein, Lawrence
    Dr. Lawrence Wein will address topics related to his research in public health and homeland security including: Preparedness and response to bio-terror anthrax attacks and to bio-terror attacks on food supply chains; Routes of transmission and infection control for pandemic influenza; Biometrics (e.g. fingerprint matching) to prevent terrorists from entering the country. The lecture will focus on modeling, policy recommendations, and implementations of these recommendations. During the presentation, Dr. Wein will also draw lessons about policy implementations from these examples and from examples from other homeland security work, including prevention of a bio-terror smallpox attack, nuclear weapons entering the country on a shipping container, nuclear weapons entering a city, and terrorist sneaking across the U.S. - Mexico border.
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    Computing, Business, and Operations Research: The Next Challenges
    (Georgia Institute of Technology, 2008-04-17) Pulleyblank, William
    There have been two consistent drivers over the last sixty years of the evolution of computing: Computer power and price/performance improve by a factor of two every eighteen months; the problems that we wish to solve require this growth in capability and more. We seem to be reaching inflection points with both of these drivers. High performance systems are turning to massive parallelism to continue the required growth in performance. New challenges are arising in business and industry that require the solution of fundamentally different problems as well as the development of new approaches to old problems. Moreover, the rapid growth of a global economy has given an unprecedented urgency to dealing with these changes. I will review these subjects and some approaches that are being applied, with varying degrees of success. In particular, I will discuss five technical problems that must be solved to enable us to successfully meet the business challenges that we will face in the future.