Dr. Christopher Monterola, is recognized of his significant contributions in the fields of complex networks, self-organization, nonlinear forecasting, granual matter, physics education and psychophysics. His work on complex networks analysis demonstrated that neural networks can benefit from ambient noise in both temporal and spatial processing of information and provided understanding of the crack propagation in woven fabrics and multilevel marketing. He and co-workers demonstrated mathematically that self-organization such as hearding of animals, firing of neurons, avalanche dynamics in granular materials can be achieved even in dissipative environment, in contrast with prevailing views. His work on analytic and numerical models with scaled experiments has helped understand the clogging and stability of granular systems. Further, he showed that nonlinear forecasting tools such as neural networks combined with statistical filtering techniques can be used in accurate forecasting of the behavior of undecided population in an opinion poll, hit songs, chalk use and author attribution, as well as for information propagated in a classroom. His latest research focused on the use of physics and statistical tools to quantify human related behavior. Dr. Monterola has mentored undergraduate and graduate students in physics. His research works are well documented in various international journals.