Prof. Dr. Donald Jacobs

Dr. Jacobs' research expertise spans the areas of Computational/Statistical Physics, Condensed Matter, Molecular Biophysics, Structural Biology, Computational Biology, Econophysics, modeling and optimization of algorithms. His research is saliently described as modeling and analyzing complex systems with the goal to understand, predict and control their emergent properties. With over 100 publications, he has made contributions in the areas of diffusion in disordered media creating anomalous long-time correlated behavior, cellular automata and Boltzmann lattice gas models for fluid dynamics, graph-rigidity applied to covalent glass networks that elucidates self-organizing dynamics, fast computational models for protein thermodynamic stability, prediction of allosteric effects in proteins, peptide design, and developed a holistic income tax system. He also developed algorithms for accurate probability density estimation suitable for high throughput analysis using non-parametric models, novel projection pursuit machine learning methods for discriminate analysis, predicting protein coding regions in DNA sequences, and discriminate analysis of EEG signals. Dr. Jacobs is developing new combinatorial optimization algorithms for quantum computing. He is interested in modeling cognitive thinking and the learning process of a system by connecting models of human thought to artificial intelligence, quantifying perception, modeling emotion, and simulating collective human behavior.