CSCE 970 (Spring 2009) Oral Presentation Schedule

Note: At the time of your talk, put your presentation on the web or bring it on a CD or USB key. You should show up early to put your presentation on the computer (or email it to me ahead of time). Doing so before the start of the session as opposed to right before your talk will speed things up for everyone. (You may use your own laptop if you wish, but things will go faster if we use a single machine.)

You are expected to attend as many talks as possible, especially those during regular class periods. Contact me if you cannot attend some talks.

You should consider your presentation's scheduled time slot final unless you have a conflict that you absolutely cannot change. This is to prevent constant modifications of the presentation schedule, which require alterations to everyone else's schedules.

Unless otherwise noted, each talk will be 15 minutes, plus 3 minutes for questions. Hence a total of 18 minutes is allotted per talk. However, this is only an approximation! Don't assume that your talk will start exactly at the time implied by the given schedule.

• Session 1
  10:30–12:20 Monday, April 27
1. Adam Voshall
   SVMs for Screening MicroRNA
2. Du Li
   Spectral Clustering Applied to Program Fault Localization
3. Pengfei Song
   Tendinopathy Discrimination by Use of Linear Discriminant Analysis
4. Brady Garvin
   Automatically Developing a Heuristic Given a Statespace in Optimization Problems


• Session 2
  10:30–12:20 Wednesday, April 29
1. Michael Gubbels
   Bayes Nets in Budgeted Learning
2. Sarah Riley
   Tolerance of Noise and Concept Shift
3. Chung-Jen Hsu
   Modeling Vehicle Infrastructure Integratrion Driving Behaviors in Highway-Rail Grade Crossings
4. Adam Wigington
   Multiple Objective Risk Analysis in Electric Power Systems
5. Katie Stolee
   Web Page Classification
6. L. D. Miller
   World of Warcraft


• Session 3
  10:30–12:20 Friday, May 1
1. Jonathan Ray
   Netflix Prize
2. Mauricio Casares and Youlu Wang
   Object Tracking in Video Sequences using Hidden Markov Models
3. Jonathan Crosmer
   HMMs to study Bach fugues
4. Adam Eck
   Multi-Agent Reinforcement Learning
5. Derrick Stolee
   A Probabilistic Model of Routing
6. Pingyu Zhang
   Data Analysis in Software Engineering

Last modified 16 August 2011; please report problems to sscott.