NSF OISE 2106013 • IRES Track II: Complexity advanced studies institute - Germany, Austria, Italy, Netherlands (Complexity-GAINs) • PI David Krakauer • Jul 1, 2021 – Jun 30, 2024
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.
NEH HT-272418-20 • Foundations and Applications of Cultural Analytics in the Humanities • PI David Kinney • Sep 1, 2020 – Aug 31, 2023
An online course on computational and quantitative methods for cultural analysis of large-scale digital sources to be followed by more advanced in-person workshops for early career scholars.
The use of computational and quantitative tools and approaches in the humanities is rapidly becoming more widespread. At the same time, there are still significant barriers preventing emerging scholars in the humanities from using these tools to generate new insights that make a genuine impact within the humanities themselves. The goal of our proposed advanced institute is to develop an online course and in-person workshop that will empower scholars in the humanities by eliminating the "black box" of computational text analysis. Participants will gain a theoretical and practical understanding of text analysis methods and the interpretation of their outputs. As such, participants will be able to extract content and derive meaning from the growing archives of digital sources, making accessible new directions in humanities scholarship. The in-person workshop in particular will be the springboard for collaborations between the next generation of analytically-inclined humanities scholars.
NSF CISE 1757923 • REU Site: Computational and Mathematical Modeling of Complex Systems • PI Cristopher Moore • Mar 1, 2018 – Feb 28, 2023
The SFI Research Experiences for Undergraduates (REU) program is a ten-week residential research opportunity in which students develop innovative research projects in collaboration with mentors. The program asks students to discard traditional disciplinary boundaries, and learn computational modeling and data analysis techniques that can apply across the physical, natural, and social sciences. This allows students to ask big questions about real-world systems using rigorous mathematical and computational methods. Projects range from simulation to machine learning to proving theorems. The program supports the goals of science education and diversity in science by emphasizing engagement with students from non-elite institutions with limited research opportunities, women, and under-represented minorities (URMs). Early career scientists act as mentors in the program, gaining valuable experience as educators in mentoring. Research performed by SFI REUs has directly advanced the progress of science, and has focused on solving problems of direct relevance to society and the national health, including vaccination strategies for whooping cough, sustainability, economics of higher education, and social network analysis, among other topics.
In every STEM field, computational and mathematical modeling are rapidly becoming essential skills: translating a real-world system into a quantitative model, designing and coding computational experiments, analyzing these experiments statistically, and comparing their results with data. Projects of this kind are an ideal opportunity for undergraduate training that builds students' technical and analytical skills, connects them with the wider scientific world, and links scientific thinking with real-world contexts and applications. The SFI REU program is designed around the strengths of being a leading transdisciplinary research center. Undergraduates are recruited from multiple departments including computer science, physics, mathematics, biology, and the social sciences, and paired with mentors from many different scientific backgrounds. Recent projects include epidemiology and public health, digital humanities and topic modeling, social network structure, cell biology and proteomics, smart cities and urban data, and statistical physics. Methods utilized range from simulation to data analysis to theorem-proving, and in many cases have produced publishable work. Throughout the summer, students are offered tutorials on the basics of data analysis, algorithms, network theory, statistics, and programming in Python and C++. Tutorials are also offered on science writing, presenting research, applying for jobs in science and picking a graduate school or industry carrer, and dealing with impostor syndrome and implicit bias.
NSF CISE 1358567 • REU Site: Computational and Mathematical Modeling of Complex Systems • PI Cristopher Moore • Apr 1, 2014 – Mar 31, 2018
The ability to mathematically model complex systems has become a prerequisite to successful science in any field. Writing a simulation is not enough; career scientists today should be able to analyze results, recognize statistical regularities, formulate conjectures, and pursue possible proofs about why these conjectures are true. The goal of this REU site is to enhance students' understanding and use of computational and mathematical modeling within their respective disciplines, and to create a new generation of mathematically and computationally sophisticated researchers. The program is designed for students from computer science, pure and applied mathematics, physics, chemistry, quantitative biology, and social science.
The proposed project provides an educational and research experience for 10 undergraduates each summer at the Santa Fe Institute (SFI), an independent, nonprofit multidisciplinary research institute dedicated to the study of complex adaptive systems, including physical, computational, biological, and social systems. SFI's REU site explores how a tier-one research institution successfully bridges the divide to under-represented minorities (URM) and to undergraduates at institutions with limited research opportunities; the aim is to provide participants with an authentic research experience in the emerging field of complex systems. The program aims for highly talented participants who attend an institution with limited research opportunities.
NSF CNS 1240992 • CS 10K: New Mexico Computer Science for All (NM CSforAll) • PI Melanie Moses • Nov 1, 2012 – Oct 31, 2017
The Santa Fe Institute (SFI), in partnership with the University of New Mexico, the Supercomputing Challenge, and other educational organizations, industry partners, and local schools, proposes a project called New Mexico Computer Science for All (NM-CSforAll). NM-CSforAll's primary targets middle and high school STEM teachers, preparing them to be future CS teachers. It offers a novel, interdisciplinary approach that uses modeling and simulation as the basis for teaching CS Principles, the proposed, new Advanced Placement (AP) CS course. Teachers first take the modeling and simulation version of CS Principles and then implement it as a dual credit course for their students. During a Spring semester-long course, the teachers investigate real-world problems, view them through the lens of complex systems--SFI's primary research area--and then model and analyze them using agent-based modeling techniques. The project uses a "flipped" classroom methodology, meaning the lecture portion of the course will be offered as online videos, while the exercise and project work will take place in the lab, face-to-face. A Summer workshop focuses on reviewing the CS content of the course, learning pedagogy, and recruitment techniques in preparation for the Fall semester implementation in the schools. The Fall implementation of the dual credit CS Principles class for high school students uses the videos developed for the teacher professional development course as lecture material and weekly "lab" session meetings led by participating teachers acting as learning coaches. (NM now requires a dual-credit, AP, or honors course for high school graduation and this course will fulfill the requirement.) NM CSforAll's secondary strategy fosters teachers' CS content learning, CS teaching pedagogy, and computer programming practice through engagement in a professional online community. NM-CSforAll's online network will include video sharing, uploading of documentation of work sessions, and social networking capabilities providing opportunities for teachers to learn from each other?s implementations of CS activities and communicate with each other, STEM educators, CS professionals and educational researchers. Teacher participants, as the co-creators of content for the site, will have shared authority, a critical factor in creating environments conducive to building knowledge about teaching and learning CS. The project evaluation will determine whether teacher professional development in CS that integrates computational modeling and analysis of complex systems, builds capacity in future CS teachers, and whether co-creation and use of an online professional development network can improve teachers' pedagogical skills and sustain their interest in CS.
NSF SBE 1005075 • REU Site: SFI's Tran-sdisciplinary Research through Computational Modeling in the Social, Biological, and Physical Sciences Program • PI Jerry Sabloff • Jun 1, 2010 – May 31, 2014
The Santa Fe Institute (SFI) hosts an REU Site focusing on the computational properties of complex adaptive systems with particular (but not exclusive) emphasis on the social sciences. The program provides a unique and transformative educational and research experience for undergraduates. SFI is a private, independent research institute dedicated to collaborative and transdisciplinary research across the biological, computational, physical, and social sciences. The REU Site focuses on fundamental scientific problems that cross scales and can be addressed by quantitative thinking, mathematical modeling and empirical data analyses. SFI, the home of complexity science, has played a seminal role in the recognition that many of the most challenging, exciting, and profound questions facing science and society (a) lie at the interfaces between traditional disciplines; and (b) raise questions of collective behavior, emergence, and multi-scale organization, all which are characteristic of complex systems. Among such questions are the physical-chemical origins of life; innovation, growth, evolution and robustness of complex adaptive systems, including organisms, ecosystems, and societies; structure and dynamics of networks in nature and society; biologically-inspired and other novel paradigms of computation; relationships between information processing, energy, and dynamics in biology and society; and growth, sustainability, and the fate of human existence. The REU students are fully immersed and engaged participants in this diverse and, for many, unique intellectual environment composed of overlapping, collaborative, interdisciplinary, and multi-generational scientific teams; in this context they team up with one or more mentors at SFI to work on meaningful complexity science research problems to which they can make a significant contribution. Activities include: participation in the Complex Systems Summer School; development of individual research projects; participation in on-going SFI workshops, working groups, symposia and colloquia; participation in the Summer Internship/Mentorship Program, acquiring teaching and mentoring skills; and presentation of research results in peer-reviewed settings.
Alumni of this SFI REU program are expected to proceed to graduate school, and into academic research and teaching professions. The program provides undergraduates with a unique opportunity to conduct scientific research in a collaborative transdisciplinary environment and to communicate that experience back to their home institutions and to carry it into their future careers. The institute and this REU Site administrators use specific and targeted plans to recruit students from traditionally under-served communities. Other dimensions of broader impacts arise as a result of the participation of previous SFI REU Site alumni (supported by institutional funds), as well as the REU students' partial participation in SFI's annual Graduate Workshop on Computational Social Sciences. All REU students are expected to co-author (with their mentors) scholarly publications.
NSF PHY 0706174 • A Broad Research Program in the Sciences of Complexity • PI Geoffrey West • Sep 1, 2007 – Feb 28, 2013
The Santa Fe Institute (SFI) is a private, independent research institute dedicated to long-term, creative, trans-disciplinary research across the physical, computational, biological and social sciences. SFI focuses on fundamental scientific problems that cross scales and can be addressed by quantitative thinking, mathematical modeling and empirical data analyses. This award supports five years of continued support for the Sante Fe Institute's (SFI) multi-disciplinary Integrative Core research program in the sciences of complexity. The award will provide partial support for SFI's visiting scientist program, workshop program, postdoctoral and graduate fellows, and educational activities. The supported work covers the following broad areas:
1. Physics of Complex Systems: Fundamental physics at SFI has spanned the principles of quantum and statistical mechanics, information theory, nonlinear dynamics and chaos, and discrete systems. These fields have provided techniques and approaches to problem solving that are useful across the sciences, and served as points of departure for the recognition of new principles. Current SFI research in physics includes: statistical physics with emphasis on self-organized states and non-conventional statistics; foundations of quantum mechanics and quantum information and control; network structure and dynamics with a wide variety of applications; and scaling and the search for quantitative, predictive theories of social and biological systems.
2. Computation in Complex Systems: SFI's research in computation has included seminal contributions in evolutionary and adaptive computation, in understanding relationships between physics and computation, in models of distributed and collective agent-based computation, and in applications of biological insights to engineered computational systems. The current work will extend SFI's contributions in the areas of physics and computation, computation in biological systems, and biologically inspired solutions to computational problems.
3. Innovation in Evolutionary Systems: Evolutionary innovations are the means by which evolution has overcome the differential between the growth of populations and the growth of the resources needed to support them. Innovation is consequently of substantial theoretical and practical concern. Research at SFI on innovation is broadly concerned with two issues: accounting for the diversity and complexity of forms in biological and technological systems; and developing a theory of transitions among forms.
4. Emergence, Organization, and Dynamics of Living Systems: Research on living systems at SFI includes: the origin of metabolism from early-earth geochemistry; the integration of energy capture, reproduction, and mutation in artificial organisms; the creation of minimal forms of life; the core principles governing ecosystem construction, stability, and measurement; the mechanisms providing stability at the social level; and applications of phylogenetic methods to vaccine development for HIV.
5. Dynamics of Human Behavior and Institutions: A continuing SFI research focus is the emergence, persistence, and demise of social institutions and their co-evolution with distinctive human behaviors, such as altruistic cooperation, out-group hostility and adaptive learning, that are typically overlooked in standard economics and other behavioral science models.
NSF OISE 0623953 • IRES in Complex Adaptive Systems with the Santa Fe Institute in China • PI David Feldman • Aug 15, 2006 – Jul 31, 2010
This IRES award supports 75 graduate students over three years from across the U.S. to participate in a 4-week, research-focused summer school on Complex Adaptive Systems in Beijing, China. The Santa Fe Institute's (SFI) Complex Systems Summer School (CSSS) in China is an international, interdisciplinary, month-long graduate program providing research training explicitly designed to prepare U.S. students for interdisciplinary, international, collaborative research in science and engineering. The CSSS was begun in 2004 and is held in partnership with Dr. Chen, Xiaosong, Professor of Physics at the Institute for Theoretical Physics, Chinese Academy of Sciences in Beijing. The U.S. PI is Dr. David Feldman, Professor of Physics and Mathematics at the College of the Atlantic in Maine. All requested funds go to offset travel costs for U.S. students.
New technologies are making available large quantities of data that were unavailable a generation ago. With these new technologies, researchers are increasingly able to use novel computational and analytic techniques to analyze large quantities of data and to study complex problems that lie outside traditionally quantitative academic disciplines. Increased computing power has also made evident the need for new analytic techniques and algorithms that are better suited to the frontier of complexity. Recognizing the new international opportunities for access to and analysis of complex data, the research community has become increasingly international in focus, with China, India, The European Union, and South America investing heavily in international research collaborations. These dual trends, the increasing interdisciplinary and international face of science, present challenges and opportunities for U.S. graduate training in research.
The SFI China Complex Systems Summer School (CSSS) meets an important need in graduate research education: teaching students tools and concepts in complex systems, and giving students hands-on experience in interdisciplinary research. The project is thus an important complement to the strong disciplinary research education offered by U.S. graduate schools. Over the three years of this project, the CSSS will develop a large network of U.S. graduate students with direct international collaborative experience who will utilize this experience to become leading international scholars.
NSF PHY 0851830 • Research Experiences for Undergraduates Site at the Santa Fe Institute • PI Geoffrey West • Mar 1, 2009 – Jun 30, 2010
This award supports the Research Experience for Undergraduates program at the Santa Fe Institute. The aim of the program is to enrich the education and research career preparation of six undergraduate students through participation in a trans-disciplinary approach to science. At the Santa Fe Institute (SFI), this approach is used to gain a transformative and integrative understanding of complex adaptive systems in the biological, social, and physical sciences. Students are immersed in a trans-disciplinary and multigenerational scientific environment; in this context they team up with one or more mentors at SFI to work on meaningful complexity science research problems to which they can make a significant contribution. Activities include: participation in the Complex Systems Summer School; development of individual research projects; participation in on-going SFI workshops, working groups, symposia and colloquia;participation in the Summer Internship/Mentorship Program, acquiring teaching and mentoring skills; and presentation of research results in peer-review settings.
NSF PHY 0353791 • Research Experiences for Undergraduate Interns at the Santa Fe Institute • PI Geoffrey West • Apr 15, 2004 – Mar 31, 2008
Students in this program are immersed in the Santa Fe Institute's multidisciplinary and multigenerational scientific environment; in this context they team up with one or more mentors to work on meaningful complexity science research problems to which they can make a significant contribution. The aim of the program is to enrich the academic and practical career preparation of these students through exposure to a transdisciplinary approach to science. Typically this approach is used to gain a better understanding of complex adaptive systems in the biological, social, and physical sciences.
NSF PHY 9987931 • Research Experiences for Undergraduates Program (REU) • PI Erica Jen • May 1, 2000 – April 30, 2003
Undergraduate students work with a Santa Fe Institute faculty mentor on an individual project focusing on some aspect of the computational properties of complex systems. SFI's broad program of research is aimed at understanding both the common features of complex systems and at comprehending the enormous diversity of specific examples. Projects focus on adaptive computation; physics, mathematics, information science, and computational aspects of complexity; economics as a complex,adaptive system; and the life sciences including modeling of the immune system, theoretical neurobiology, genetic data analysis, theoretical ecology, and models of protein folding. This program is highly individualized. Each student works with one or more faculty mentors on a specific self-selected project. Participants are expected to be in residence approximately 10 weeks, within the approximate mid-May to mid-August window.
NSF PHY 9970158 • A Broad Research Program in the Sciences of Complexity • PI Ellen Goldberg • Sep 1, 1999 – Aug 31, 2002
The Santa Fe Institute (SFI) will conduct multidisciplinary research in the science of complexity. SFI will run a visiting scientist program, a workshop program, and maintain its summer school on complexity and its education and outreach activities. The organizing themes central to all the SFI workshops and the visitor program include evolutionary dynamics, integrating form and organization with dynamics, robustness of natural and social systems, and complex networks dynamics. Researchers involved in the SFI activities will come from many disciplines, including biology, physics, mathematics, computation, and the social behavioral, and economic sciences. The techniques of complexity, chaos, and adaptive systems provide the unifying intellectual basis for the proposed studies. Graduate student and postdocs are integral to all of the SFI activities. SFI also will serve as the host for an REU Site program and a program that will provide broadening, multidisciplinary research experiences to physics graduate students.
NSF PHY 9531317 • Proposal to Support and Undergraduate Research Site at the Santa Fe Institute • PI Erica Jen • Feb 15, 1996 – Jan 31, 2000
The Santa Fe Institute will continue its REU program. The site will select a limited number of highly motivated and talented undergraduates who can benefit from exposure to the rich interdisciplinary mix of ideas at the Institute. Women and minorities will especially be invited to apply. Senior faculty mentors will be selected for their interest in the program and each undergraduate will be matched with one or more mentors who have research problems of real interest to the student and to which the student can make a significant contribution. Other resident scientists will be encouraged to take a regular interest in the intellectual development of the interns. The students will be encouraged to participate fully in the intellectual life of the Institute by attending colloquia and seminars and through informal discussion of their work with other resident researchers. Where appropriate, publication of scientific papers, attendance at workshops, and release of student-developed software will be encouraged by SFI. During each student's residency he will make a SFI colloquium presentation, compile a written summary of his work, and frequently consult with the program director. Students are encouraged to remain in contact with the Institute and their mentors as their careers develop, and, if appropriate, to return for subsequent scholarly visits.
NSF PHY 9300206 • Support of an Undergraduate Research Site at Santa Fe Institute • PI Leonard Simmons • Mar 15, 1993 – Aug 31, 1996
This grant will support an REU Site at the Santa Fe Institute, so that SFI can expand its existing program which provides undergraduates with the opportunity for research in the field of adaptive computation in particular and complex adaptive systems in general. Such studies are particularly appropriate as an entry point for undergraduates into research. The program will be open to students in a broad range of the physical, biological, and computing sciences.