IGERT - Program in Nonlinear Systems

康奈尔大学非线性系统IGERT项目支持复杂非线性系统领域的研究生教育和研究。该计划的研究部分将围绕跨学科小组(IRTG)组织，该小组由拥有理论、计算和经验科学专业知识的教职员工组成，他们将共同指导研究生的同伴项目。最初的IRTG的研究领域包括应用领域，包括(I)网络(社会网络、基因网络、互联网、电网)；(Ii)基因调控(细胞信号和基因表达网络)；(Iii)移动机器和生物体(手动灵巧和运动控制)；以及(Iv)生物模式形成(心脏电生理学)。非线性科学已成为跨学科研究的榜样。来自动力系统理论的原理揭示了科学和工程领域中看似不相关的现象的共同特征。这个项目的智力价值在于将非线性动力学中的成功策略扩展到面对日益复杂的系统。这项研究的一个主要目标是理解系统，特别是那些出现在生命科学中的系统，如何能够超过它们各部分的总和。例如，将通过结合机械设备、观察人类和动物行为以及计算机模型来研究腿部运动和手动灵活性。这项研究的更广泛影响将是在改善机器人的性能和身体伤害的治疗方面。将探讨的另一个主题是网络体系结构如何影响系统的动态。小世界网络的概念是由IGERT计划的创始人史蒂夫·斯特罗加茨和他的学生提出的，已经影响了对生物、社会和通信网络的研究。将该研究成果应用到互联网上，有助于高效的网络搜索。总体而言，该程序将在开发预测复杂系统动力学的方法方面产生广泛影响，充分考虑潜在的网络结构并广泛使用实验数据。IGERT计划的主要机制是让博士生在学习早期参与非线性系统研究。该计划让学生参与研究的概念阶段，并鼓励教师在IRTG学生的共同指导下发展长期合作。该计划最直接的影响是培养具有广泛兴趣和专业知识的新一代科学家。用一位前IGERT研究员的话说，“参加IGERT项目的研究生可以相当流利地学习说两个或多个领域的语言，所有学生都被介绍给一个共同的数学基础，这样即使那些不分享特定领域语言的人也可以进行有意义的互动。”IGERT是一个NSF范围的项目，旨在应对培养具有跨学科背景、选定学科的深厚知识以及满足未来职业需求所需的技术、专业和个人技能的美国博士科学家和工程师的挑战。该项目旨在通过建立创新的研究生教育和培训新模式，在超越传统学科界限的合作研究的肥沃环境中，催化研究生教育的文化变革。在该计划的第六个年头，由NSF支持的共同跨越科学和工程领域的项目将被授予机构奖项。

The Cornell University IGERT Program in Nonlinear Systems supports graduate education and research in the area of complex nonlinear systems. The research component of the program will be organized around interdisciplinary groups (IRTG) comprising faculty with expertise in theoretical, computational and empirical science, who will jointly mentor graduate student fellow projects. The research areas of the initial IRTG, including areas of applications, are (i) networks (social networks, gene networks, internet, electric power grid); (ii) gene regulation (cell signaling and gene expression networks); (iii) moving machines and organisms (manual dexterity and control of locomotion); and (iv) biological pattern formation (cardiac electrophysiology).Nonlinear science has been a role model for interdisciplinary research. Principles arising from dynamical systems theory have revealed common features in seemingly unrelated phenomena across the breadth of science and engineering. The intellectual merit of this project lies in the extension of successful strategies employed in nonlinear dynamics to confront increasingly complex systems. A primary goal of the research is to understand how systems, especially those arising in the life sciences, can be more than the sum of their parts. For example, legged locomotion and manual dexterity will be studied through a combination of mechanical devices, observation of human and animal behavior and computer models. The broader impacts of this research will be in improving the performance of robots and the treatment of physical injuries. Another theme that will be explored is how network architecture influences dynamics of a system. The concept of small world networks, developed by the founder of this IGERT Program, Steve Strogatz and his students, has already influenced research on biological, social and communication networks. Applied to the internet, the results of this research facilitate efficient web searches. In general, the program will have broad impact in developing methods to predict the dynamics of complex systems, taking full account of underlying network structures and making extensive use of experimental data. The primary mechanism of the IGERT program is the engagement of Ph.D. students in nonlinear systems research early in their studies. The program involves students in the conceptual phases of research, and it encourages faculty to develop long term collaborations, stimulated by their joint mentorship of students in the IRTG. The most direct impact of the program is in training a new generation of scientists with broad interests and expertise. In the words of a former IGERT fellow, "graduate students who go through the IGERT program learn to speak the language of two or more fields with considerable fluency, and all students are introduced to a common mathematical foundation so that even those who do not share the language of a specific field can interact meaningfully."IGERT is an NSF-wide program intended to meet the challenges of educating U.S. Ph.D. scientists and engineers with the interdisciplinary background, deep knowledge in a chosen discipline, and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing innovative new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries. In this sixth year of the program, awards are being made to institutions for programs that collectively span the areas of science and engineering supported by NSF.