SFI's Melanie Mitchell receives the 2023 Senior Scientific Award

SFI Professor Melanie Mitchell has been awarded the 2023 Senior Scientific Award by the Complex Systems Society for her exceptional contributions to various fields, including artificial intelligence and complexity science, as well as her efforts in educating a broad audience about complex systems. Mitchell's extensive work, including the creation of Complexity Explorer, has significantly impacted the understanding and promotion of complexity science and AI research.

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A new era of personalized modeling through digital twins?

While researchers are on the cusp of creating computer models for entire organs, precision healthcare applications using digital twins are still theoretical. Karen Willcox, an SFI External Professor and University of Texas aerospace engineer, is helping to convene a National Science Foundation-sponsored workshop at SFI, October 12–13, to make this new type of modeling technology a reality.

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Study: "Assembly Theory" unifies physics and biology to explain evolution and complexity

An international team of researchers has developed a new theoretical framework that bridges physics and biology to provide a unified approach for understanding how complexity and evolution emerge in nature. This new work on "Assembly Theory," published in Nature, represents a major advance in our fundamental comprehension of biological evolution and how it is governed by the physical laws of the universe.    

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Sharing visual categories through language

As children, we learn categories through visual examples, verbal explanations, or both, and are often guided by “teachers” — perhaps a parent or other adult. In contrast, academic research has primarily studied non-pedagogical learning where there is no active teacher, and learning based on visual examples, omitting verbal-based category learning. A recent paper in Cognition by Arseny Moskvichev and co-authors aims to close this gap.

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SFI welcomes Postdoctoral Fellow Andrew Stier

How much do city environments constrain human behavior? What aspects of a city’s organization affect the psychology and mental health of its inhabitants? Scientific theories anchored in psychology that explain how city spaces shape human behavior are sparse. Omidyar Postdoctoral Fellow Andrew Stier works at the intersection of psychology and urban science to build theoretical models that examine how individuals and large groups adapt to and design city spaces.

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New study helps explain why people cooperate when no one is looking

That strong urge many people feel to abide by social norms even when it is individually harmful may have its roots in Darwinian fitness, according to a new study in Behavioral Ecology and Sociobiology. The research uses agent-based modeling to provide an evolutionary mechanism that helps explain what keeps people cooperating even when no one is looking.

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SFI welcomes Postdoctoral Fellow Harrison Hartle

The study of mathematical models can provide insight into the structure and function of complex systems. However, even simple models can often be quite difficult to analyze, and meaningfully connecting models to real-world data is more challenging still. Omidyar Postdoctoral Fellow Harrison Hartle’s research expertise is in mathematical and computational modeling. He is interested in advancing the study of generative models for complex systems with the goal of constructing practically applicable and meaningfully interpretable models for real-world data. 

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Workshop explores general patterns for lifespan across scales

A September 27–29 workshop, the Complex Time General Conference on Immortality, meets to explore general patterns for lifespan across scales, from organisms, the mind, and behavior, to civilizations and star systems. The organizers hope to challenge preconceptions about immortality and, eventually, develop a general theory of longevity. 

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Study: an overlooked weakness in a powerful machine learning tool

In the last two decades, researchers have reported success modeling high-dimensional chaotic behaviors with a simple but powerful machine-learning approach called reservoir computing. A new paper in Physical Review Research identifies limitations to reservoir computing and suggests a kind of catch-22 that can prove hard to circumvent, especially for complicated dynamic systems. 

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Two External Professors receive federal funds for disease-prediction research

The Centers for Disease Control and Prevention (CDC) has committed more than $250 million to become better prepared for disease outbreaks like COVID-19 — and they’re turning to two SFI researchers, Sam Scarpino of Northeastern University and Lauren Ancel Meyers of the University of Texas at Austin (UT), to help make it happen.

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Study: Visual Analogies for AI

The field of artificial intelligence has long been stymied by the lack of an answer to its most fundamental question: What is intelligence? To address questions about intelligence in AI, we need concrete tasks to pin down and test the notion of intelligence, argue SFI researchers Arseny Moskvichev, Melanie Mitchell, and Victor Vikram Odouard in a new paper in Transactions on Machine Learning Research.

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SFI welcomes Postdoctoral Fellow Saverio Perri

In a complex system, small, local changes can create a cascade of unexpected consequences in other parts of the system. Choices that seem immediately prudent might prove less ideal in the long term. Applied Complexity Fellow Saverio Perri is interested in the unexpected ways that sustainability transitions might impact both social and ecological systems. 

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SFI welcomes Postdoctoral Fellow Katrin Schmelz

Incoming Omidyar Fellow Katrin Schmelz grew up in East Germany, mere kilometers from the border with West Germany. The experience has shaped her research questions into how experiences of state control impact how people respond to other restrictions throughout their lives and how individual behaviors and values coevolve with societal institutions and policies.

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Meeting explores collective adaptation in a turbulent world

The past 20 years have seen rapid changes in our social networks, and our individual behaviors are now maladapted. To respond to these changes as a society, we first need a better understanding of how groups alter their decision-making strategies and beliefs to cope with emerging problems. A September 12–14 workshop, part of SFI’s CounterBalance Series and funded by Siegel Family Foundation, is convening scientists from a range of biological, social, and physical sciences, and senior representatives from civic organizations and the tech industry, to discuss the challenges and potential directions forward. 

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SFI welcomes Complexity Postdoctoral Fellow Kerice Doten-Snitker

Hoping to finish the most comprehensive spatial database on medieval and modern Germany, Complexity Postdoctoral Fellow Kerice Doten-Snitker enters SFI intending to weave complexity science into her research. Doten-Snitker’s research explores how the formation of states and institutions pave the way for social constructs of race and ethnicity to emerge. She completed her Ph.D. in sociology at the University of Washington.

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SFI welcomes Applied Complexity Fellow Seungwoong Ha

Machine-learning tools have powerfully accelerated the process of doing science. They can sort through and analyze vast sums of data, revealing insights and connections about the world never before possible. But could we ever fully automate the scientific process?  Could we make an AI physicist? It’s a question that captured Seungwoong Ha, an incoming Applied Complexity Fellow, as a student at Korea Advanced Institute of Science and Technology (KAIST) where he completed his B.S. and integrated M.S. and Ph.D., all in physics. 

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SFI welcomes Complexity Postdoctoral Fellow Anna Guerrero

SFI welcomes Complexity Postdoctoral Fellow Anna Guerrero, whose research focuses on the use of images in biology. She uses a historical and philosophical lens to docuent how biologists use the concept-to-image cycle to learn about the physical world. 

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