Speaker: Joshua Woodard, Cornell University
Abstract: The increased availability of high resolution biophysical, demographic, and economic data, coupled with dramatic increases in storage and computational capacities, have created exciting new opportunities for data-driven scientific discovery. With these opportunities, however, come new challenges requiring unprecedented levels of collaboration across scientific disciplines. Adoption of state-of-the-art data-analytic tools and methods by social and biophysical scientists, and incorporation of behavioral, socioeconomic, and biophysical structure by computational scientists in “Big Data” statistical models, represent critical bottlenecks for advancing data-driven discovery. The purpose of this talk is to review some of these current developments with special emphasis on multidisciplinary perspectives.