Professor James A. Reggia

James A. Reggia, M.D., Ph.D. is Professor at Department of Computer Science and at Institute for Advanced Computer Studies with a joint appointment at the Department of Neurology, all at the University of Maryland.
 
Jim’s research group focuses on studying and understanding 1) the underlying principles of biological computation, and how these principles can be adopted or modified to extend contemporary computer science methods, and 2) automated causal reasoning, such as abductive inference and Bayesian/belief networks.
 
Several properties of biologically-inspired computing separate it from more traditional computer science, giving hope that new robust and adaptive software methods can be developed. Examples of this type of computing include neural computation, evolutionary computation, artificial life, self-replicating machines, artificial immune systems, ant colony optimization, L-systems, artificial societies, and swarm intelligence. His group has worked and/or is working in the following areas:

• neural computation
• multi-agent artificial life systems
• evolutionary computation
• cellular automata models of self-replication

Jim is also focusing on automated causal reasoning using more traditional methods in artificial intelligence. The goal of this research is to model human cognition as a means of generating useful automated reasoning systems. His group has worked and/or is working in the following areas:

• knowledge acquisition
• abductive reasoning
• Bayesian classification and networks
• parsimonious covering theory

Jim contributed to Neurocomputing Research Developments, coedited Neural Modeling of Brain and Cognitive Disorders and Computer-Assisted Medical Decision Making Volume 1 (Computers and Medicine), and coauthored Abductive Inference Models for Diagnostic Problem-Solving (Symbolic Computation / Artificial Intelligence). His papers include: Systematically Grounding Language through Vision in a Deep, Recurrent Neural Network, Plausibility of diagnostic hypotheses: The nature of simplicity, and Progress in the simulation of emergent communication and language.
 
He earned his M.D. at the University of Maryland at Baltimore in 1975 and his Ph.D. at the University of Maryland in 1981.