Jeehyuk Park,
Ph.D student
Industrial and Systems Engineering,
Texas A&M University

"The choice of alternatives in wager"
Short Bio:
Jeehyuk Park earned his Bachelor of Science and Master of Science degrees in Industrial Engineering from Kangnung National University in South Korea. The concentrated areas in Master degree were operations research, simulation and scheduling with thesis "A study on the Genetic Algorithms for the scheduling of both coarse and fine grain types of Parallel Computation Systems". He served in the Army as a Korean Augmented To US Army (KATUSA) between 1998 and 2000. After completion of his service, a project manager was the first job in SDL Alpnet Inc. korea branch located in Seoul, South Korea. He joined Ph.D. degree program of Industrial and Systems Engineering, Texas A&M University in 2002 and passed a Ph.D defense last semester. His research interests include wagering, applied probability and optimization algorithms.

Seminar Abstract:
Design, deployment and operation of technology often require choosing from alternatives that have uncertain rewards with investments. It is reasonable to consider random variables for representing the time and magnitude of such rewards. Then, the choice of alternative becomes a stochastic problem, which cannot be simple in general. In addition, the gambler may lose the entire investment in the worst case. Thus, if we define wagering as an activity to bet money on one of the alternatives the rewards of which appear over time with uncertainty, wagering is difficult but important issue.

There are two main issues that must be figured out for the choice of alternatives in wager. The first one is how to represent the value of alternatives in a wager, in other words, how to characterize a risk of a wager alternative. And the other is how to select the best alternative with this risk characterization. Also, we may think the situation that we cannot decide the preferable alternative with given information for uncertain rewards.

In this talk, the speaker will present a risk assessment of an alternative associated with a set of probability measures that capture the dynamics of random rewards. The principles which support selecting the best one among the risk encumbered wager alternatives and the corresponding computational framework will be described. The concluding form in the framework is often non-convex mathematical programming. A Markov Chain Monte Carlo (MCMC) used to approximate the solutions of this optimization problem will be presented, along with an implementation example. The speaker will conclude this talk by discussing future extensions of this research as well as viable applications.

Jane Stephens,
Assistant Professor
Science & Engineering librarian,
Evans Library Reference

Patricia Alford,
Doctor
Work in the Science and Engineering Reference Services
at the Evans Library

"Interactive seminar on conducting an effective graduate level literature review"
Short Bio:
Jane Stephens received a BA from Boston University, an MLIS (library science) from University of Texas, Austin and, an M.Ed. degree in educational psychology from Texas A&M University. Prior to receiving her MLIS degree, Jane worked in the technical services division of the Evans Library, Texas A&M. After receiving her MLIS, she joined Evans Library Reference as a Science & Engineering librarian where she has been since 1999. As a Lecturer, and recently Assistant Professor, she is liaison to and provides collection development, instructional services and reference expertise for the Aerospace Engineering, Industrial & Systems Engineering and Recreations, Parks & Tourism Sciences departments.

Seminar Abstract:
After more than 20 years as a research and clinical veterinarian caring for nonhuman primates, Dr. Alford pursued interests in research methodology and informatics by obtaining a M.S. in epidemiology from the TAMU College of Veterinary Medicine and a M.S. in information science from the UNT School of Library and Information Science. She began working at the Evans Library as a part-time graduate assistant in the electronic reference area, and has been full-time in the Science and Engineering Reference Services since 1999.