Complexity in Science/Technology/Society

Objective: To network a collective from a broad range of disciplines and research institutions for forecasting and cyber-enabled discovery.

Significance: Discovering stable-solution strategies for forecasting and achieving goals within short-to-medium time horizons becomes more complicated as complexity increases. Time-series forecasting methods are not stable and lack a comprehensive theory of stability.

Long Range Goal: Evaluate novel hybrid frameworks for solving realistic problems within a secure public-accessible cyber space.

Collaborators: Valeriy Gavrishchaka (Alexandra Investment Management), David Hartley (Georgetown University School of Medicine), Mark Koepke, Dimitris Vassiliadis

The objective of this research group is to link researchers from a broad spectrum of traditional disciplines and from a variety of research institutions into a loosely networked collective for the purposes of intellectual cooperation and joint fund raising. The motivation for this research group comes from the well-known fact that intra-disciplinary and inter-disciplinary collaboration multiplies the number of research breakthroughs and significantly enhances the number and success rate of research proposals. The long-term goal of this research group is to develop a self-sustaining, productive, internationally recognized collaborative laboratory from which new ideas can be investigated, vetted, and promoted at meetings, in the literature, and within research proposals. This research was initiated with four founding faculty (Koepke, Gavrishchaka, Vassiliadis, and Hartley) and will incorporate additional researchers as the funding base grows and the intellectual advancements become recognized by others. Joint proposals have been submitted and periodic joint visits to each others research groups occur.

Dr. Gavrishchaka, PhD, Adjunct Associate Professor in WVU Physics, is a theoretical physicist with a background in analytical theory and numerical simulations. His specialty is the physics of plasmas and space weather, development of systems for automatic discovery of market strategies, and application of advanced pattern recognition and ensemble-learning algorithms to real life problems such as space-weather forecasting and such as analysis of daily and intraday market data. He has extensive experience with simple analytical models, complex simulations, pure data-driven empirical models (including neural nets), and boosting-based intelligent frameworks capable of very efficient combination of all the above models (but with an emphasis on simple well-understood models as base models).

Dr. Vassiliadis, PhD, Research Associate Professor in WVU Physics, is a theoretical physicist with a background in modelling and in computational space physics. He has extensive experience with investigating magnetospheric and ionospheric plasma processes and developing space weather forecasting tools. He analyzes theoretically various results from space observations and laboratory plasma experiments.

Dr. Hartley, PhD and MPh, Research Associate Professor, Georgetown University School of Medicine, is an expert in infectious disease modeling. He leads a diverse team that supports the Global Argus Project research and development program. The team concentrates on linguistics, data mining, decision science, data sharing technology, global information systems, and information representation. Dr. Hartley's other research interests include mathematical epidemiology, the ecology of infectious disease, antibiotic resistant infections, food supply safety, and multiple topics in bioterrorism defense. For example, he explores novel mathematical models of the epidemiology of Rift Valley Fever (RVF) [Gaff, Hartley, and Leahy, Electron. J. Diff. Eqns. 2007, 1-12 (2007)] and other infectious diseases using nonlinear dynamics. RVF is an Old World, mosquito-borne disease affecting both livestock and humans. The model is an ordinary differential equation model for two populations of mosquito species, with one species transmitting vertically and the other species not transmitting vertically, and for one livestock population. The stability of the disease-free equilibrium is analyzed and tested for stability-sensitive parameters. Future outbreaks in the Old World are predicted and threats of introduction into the New World are assessed. He also investigates terrorist-inflicted injuries related to radiation and nuclear sources as well as the hyper-infectivity of cholera and anthrax, both bioterrorism-related diseases.