Our people

Specialty areas:

High-performance computing, scientific computing, K-12 CS education, diversity in computing

Specialty areas:

Genetic algorithms, evolutionary computation, swarm systems

Genetic algorithms solve problems using the principles of Darwinian evolution.  The algorithm maintains a population of candidate solutions to the problem which it evolves over a number of generations, using algorithmic analogs to reproduction, mutation, and survival of the fittest.  The challenge is to encode the problem in such a way that allows the evolutionary progress to be meaningful and to implement genetic operators that are effective.

A newer area of inquiry for me is decentralized swarm-based systems.  Modeled by natural swarms, such as bees and ants, swarm-based systems use a large number of small, inexpensive computational agents to solve problems.  These agent can be robots, simulations, or other software programs.  The large number of agents in a. swarm provides redundancy and, therefore, protection against agent loss.  The key to making these systems work is an effective mechanism allowing the agents to make independent decisions about how to contribute to the overall goal of the swarm.

Specialty areas:

Software Engineering, Formal Specification of software systems

Specialty areas:

Human-Robot Interaction, Human-Computer Interaction

Specialty areas:

Localization in Cellular Network and Wireless Sensor Network, Sensor Fusion, Optimal State Estimation.