IRES Track II: Complexity advanced studies institute - Germany, Austria, Italy, Netherlands (Complexity-GAINs)

点击翻译按钮获取中文摘要

Many challenges in the world today – disease dynamics, collective and artificial intelligence, belief propagation, financial risk, national security, and ecological sustainability – exceed traditional academic disciplinary boundaries and demand a rigorous understanding of complexity. Complexity science, as pioneered at the Santa Fe Institute (SFI) and elsewhere, aims to quantitatively describe and understand the adaptive, evolvable and thus hard-to-predict behaviors of complex systems. One of the greatest lessons of 2020 is how critical this kind of understanding is to our society. We require a scientific workforce capable of integrating theory from biology, social sciences, physics and computer science with mathematical and computational modeling. Despite the centrality of complex systems and the importance of diverse perspectives and international collaboration in addressing the challenges facing our world, purposeful opportunities for PhD student training in these areas are sparse. SFI’s 14-day Complexity Advanced Studies Institutes (ASIs)—based centrally in the EU research network—fills this gap by introducing 18 US PhD students and their EU counterparts to the theory and practice of complex systems modeling in an internationally collaborative setting. After completing Complexity ASIs, participants serve as catalysts in the US scientific workforce, advancing the use of complex systems science to solve imminent problems facing our society and the world.Complexity ASIs leverage the transdisciplinary ideas, expert faculty, proven training capacity and international reach of SFI, in collaboration with four leading complex systems research institutions in Germany, Austria, Italy and the Netherlands (GAINs) and located centrally in Vienna, Austria. The Complexity-GAINs partnership expands the faculty’s expertise and perspective, gives students access to influential international research partners, and strengthens collaboration among institutions. Students gain foundational knowledge and practice in modeling complex systems of interest through a combination of lectures, discussions, skills tutorials, peer-group problem-solving and hands-on mentored research. The annual program, operating over three years, focuses on different systems each year—intelligent systems, social-behavioral systems, ecosystems—and provides students with broadly applicable tools to recognize and define the universal properties of all complex systems. Following participation in Complexity-GAINs ASIs, PhD students are equipped to (1) describe and better predict the behavior of a complex system through mathematical or computational modeling; and (2) leverage interdisciplinary, international partnerships to achieve shared research and applied goals. The international nature of the program is essential to both goals and will ensure that early-career US researchers are prepared to address complex systems beyond disciplinary and geographic boundaries. An associated outcome of the program is the establishment of a complex systems curriculum and accompanying instructional content for broad dissemination.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.