Research Experience for Undergraduates

UTEP REU Summer Site in Applied Intelligent Systems

Sample Research Projects

The unifying research theme for this REU will be the use of intelligent system techniques, including machine learning, data mining, optimization, and image analysis, to solve relevant data analysis problems in science and engineering fields. Students will be able to choose from the following list, according to their interests and abilities:

Discovering the Patterns of Interaction in Spoken Dialog

Spoken dialog systems today are not as responsive as one would like; indeed, their patterns of interaction are generally perceived as rigid and robotic. Improving this requires a better understanding of what patterns of interaction are normal in human-human interaction. In this project we will develop tools and techniques for both semi- and fully-automated analysis of medium to large dialog data corpora, and measure the value of the discovered patterns for dialog systems.

Generating Test Cases for Pairwise Testing Using Genetic Algorithms

Pairwise testing is a combinatorial testing technique that tests all possible pairs of input values. Although, finding a smallest set of test cases for pairwise testing is NP-complete, pairwise testing is regarded as a reasonable cost-benefit compromise among combinatorial testing methods. The objective of this project is to formulate the problem of finding a pairwise test set as a search problem and apply a genetic algorithm to solve it. A genetic algorithm is a technique that simulates the natural process of evolution and is known to be very effective for finding solutions for problems with a huge search space and complexity. The project will also develop an open-source program that could be used as a framework for generating pairwise test sets using genetic algorithms.

Automated Identification of Foreign Accents in Speech

In many security applications, it is desirable to determine a person's native language from speech in a second language. The first part of this project will consist of developing a small corpus of English spoken by speakers of English as a second language with different native languages (for example, Spanish, Chinese, Arabic, Portuguese, and French). In the second part, various features and learning algorithms will be evaluated to determine the degree to which native languages can be accurately identified automatically and the features (phonemes, prosody, etc.) that allow this identification.

A Survey of Fuzzy Measure Extraction Techniques and Design of a Hybrid Optimization Technique for Multi-criteria Decision Making

At the heart of decision making are very often multiple criteria. It can be challenging to combine them properly to take into account potential dependency between criteria and to make a sound decision. Fuzzy measures combined into a Choquet integral are an option of choice to express dependencies and reach a sound decision. However, fuzzy measures are hard to determine: either the user has to exhaustively describe it (which can be unreasonably long and irrelevant) or the measure can be extracted from some sample data (by solving an optimization problem).

GPU Implementation of Tracking Algorithms

Modern vision-based tracking algorithms usually use a version of the condensation or particle filter algorithm, which approximates the distribution of possible configurations of the objects of interest using a discrete set of hypotheses commonly called particles. The likelihood of each particle has to be evaluated at every tracking cycle, and in complex domains thousands of particles are needed to properly approximate the target probability distribution. The goal of this project is to implement a vision-based tracker using a Graphics Processing Unit (GPU) in order to evaluate hundreds or thousands of particles in parallel, allowing real-time tracking of multiple complex objects.

Analysis of Animal Behavior Using 3D Computer Vision

Behavior analysis of laboratory animals is a tedious process that has to be performed by visual observation. The goal of this project is to develop a software system based on the Kinect 3D image-based sensor to autonomously monitor and analyze the behavior of laboratory rats.

Analysis of Planetary Images

The Cassini spacecraft took thousands of images of Saturn and its rings and moons. Unfortunately, to date this image dataset is poorly organized, which prevents the scientific community from fully exploiting it. This project consists of developing an image analysis system to classify and perform a preliminary analysis of this large image dataset.

Game Theory for Homeland Security

A common problem in protecting infrastructure and networks against attackers is making decisions about how to allocate limited resources to protect the most important targets. This work focuses on using game-theoretic modeling to understand these decisions, find optimal randomized (unpredictable) policies for resource allocations, and give recommendations to police or other end users. This project will address specific issues in resource allocation for border security.

Agent Technologies for the Smart Grid

The world is undergoing dramatic changes in the ways that energy is generated, distributed, and used. Intelligent agents are a critical technology in managing the increasingly complex and decentralized energy systems that are evolving. These technologies, often called the "smart grid", have the potential to dramatically improve the efficiency and reliability of future energy markets. This project will focus on developing a trading agent to compete in the "Power TAC" game, a new scenario this year that is part of the annual Trading Agent Competition. More information about the Trading Agent Competition and Power TAC is available at http://tradingagents.org and http://www.powertac.org.

Compression of Meteorological Data

Environmental monitoring stations are generation enormous amounts of data that pose significant challenges for transmission and storage. This project deals with the use of machine learning approaches to attain very high compression rates with minimal information loss. This research would build on similar approaches we have applied successfully in the areas of medical image compression and surveillance.

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