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

当今世界的许多挑战——疾病动态、集体和人工智能、信仰传播、金融风险、国家安全和生态可持续性——超越了传统的学科界限，需要对复杂性有严格的理解。复杂性科学，作为圣达菲研究所（SFI）和其他地方的先驱，旨在定量地描述和理解复杂系统的适应性、可进化性和难以预测的行为。2020年最大的教训之一就是这种理解对我们的社会是多么重要。我们需要一支能够将生物学、社会科学、物理学和计算机科学的理论与数学和计算建模相结合的科学队伍。尽管复杂系统处于中心地位，多样化的观点和国际合作在解决我们世界面临的挑战方面具有重要意义，但在这些领域培养博士生的有目的的机会很少。SFI为期14天的复杂性高级研究所（ASIs）位于欧盟研究网络的中心，通过在国际合作环境中引入18名美国博士生和他们的欧盟同行来研究复杂系统建模的理论和实践，填补了这一空白。完成复杂性ASIs后，参与者将成为美国科学界的催化剂，推动复杂系统科学的使用，以解决我们社会和世界面临的迫在眉睫的问题。复杂性ASIs利用SFI的跨学科思想，专家教师，成熟的培训能力和国际影响力，与德国，奥地利，意大利和荷兰的四个领先的复杂系统研究机构（gain）合作，位于奥地利维也纳市中心。复杂性-增益的合作伙伴关系扩大了教师的专业知识和观点，使学生有机会接触有影响力的国际研究伙伴，并加强了机构之间的合作。学生通过讲座、讨论、技能教程、同伴小组解决问题和实践指导研究的组合，获得建模感兴趣的复杂系统的基础知识和实践。这个为期三年的年度项目，每年关注不同的系统——智能系统、社会行为系统、生态系统——并为学生提供广泛适用的工具，以识别和定义所有复杂系统的普遍属性。参与复杂性增益ASIs后，博士生将具备(1)通过数学或计算建模来描述和更好地预测复杂系统的行为；(2)利用跨学科的国际伙伴关系来实现共同的研究和应用目标。该项目的国际性质对这两个目标都至关重要，并将确保早期职业的美国研究人员准备好解决超越学科和地理界限的复杂系统。该方案的一个相关成果是建立一个复杂的系统课程和伴随的教学内容广泛传播。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.