The Santa Fe Institute is an institution that draws renowned scientists and researchers from institutions, government agencies, research institutes, and private industry. The Institute’s research is integrative and there are no formal programs or departments. The two dominant characteristics of the SFI research style are commitment to a multidisciplinary approach and an emphasis on the study of problems that involve complex interactions among their constituent parts.

SFI is dedicated to basic research. The Institute is not engaged in directed or applied research, and does not perform research for hire. For those projects requiring massive computer processing power, the Institute has relationships with both Los Alamos National Laboratory and the University of New Mexico. In addition, SFI has a parallel processing machine powered with 64 Intel microprocessors on site.

As many as 50 scientists and researchers can be accommodated at SFI for visits of varying intervals of time. While there are no permanent faculty, there is a mix of residential research professors (up to six-year appointments), postdoctoral fellows, graduate students, visitors, and external faculty members. SFI considers itself an "institute without walls." This means that although people come to visit, attend workshops, and collaborate, they return to their home institutions, and research continues in a distributed fashion among scholars in different places.

Although we note several current research themes, any "snapshot" of Santa Fe Institute researchers and activities is by definition fuzzy. Topics frequently overlap, making a project’s assignment to a single theme area more or less arbitrary. As part of SFI’s metabolism, loosely organized researcher groups are constantly forming and reforming as topics mature. Further, individuals are often involved in multiple projects. Finally, although the SFI campus plays a central role in the life of its far-flung community, much work also takes place off-site as collaborators participate from their home institutions. The projects and researchers noted on these pages can, at best, be considered a representative sample.

Dynamics of Human Behavior and Institutions

A priority focus of research at the Institute continues to be 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 — typically overlooked in standard economic and other behavioral science models. read more...

Information Processing & Computation in Complex Systems

Computation has been a central theme of SFI research since its inception, including seminal contributions in evolutionary and adaptive computation, relationships between physics and computation, models of distributed and collective agent-based computation, and applications of biological insights to engineered computational systems. read more...

Innovation In Evolutionary Systems

Thomas Malthus’s concern over the differential between the growth of populations and the growth of the resources to support them underlies both Charles Darwin’s theory of natural selection, and much of traditional economics. But Malthus was wrong, at least over the long term.  Contrary to the predictions of the logistic growth model of Pearl and Reed in 1920, the population of the US did not top out at 197 million and has just reached 300 million. read more...

Living Systems Dynamics

Research on living systems at SFI spans: 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. read more...

Physics of Complex Systems

Fundamental physics is core area of research at SFI. It spans 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. For instance, the application of self-organization to dynamical critical states arose from the study of granular systems, and agent-based simulation introduced a process-based generalization of Monte Carlo methods. read more...