Complex Systems and Biophysics

Michelle Driscoll

Professor Driscoll is a soft condensed matter experimentalist, and her research lies at the junction between soft-matter physics and fluid dynamics. Her lab focuses on understanding how structure and patterns emerge in a driven system, and how to use this structure formation as a new way to probe nonequillibrium systems. We study emergent structures in a diverse array of driven systems, from the microscopic to larger-scale.  By developing a  deeper understanding of patterns and structures which emerge dynamically in a driven material, we can learn not only how these structures can be controlled, but also how to use them to connect macroscopic behavior to microscopic properties.

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Pulak Dutta [Dutta Research Page]

Professor Dutta is studying the interface between soft and hard materials. These are common in biology: many organisms grow inorganic components (biominerals) to add mechanical strength and also for sensing applications. Prof. Dutta's group uses bioinspired techniques to grow inorganic crystals at ordered organic surfaces, which they study using X-ray scattering, atomic force microscopy, and other techniques.

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John F. Marko [Marko Laboratory Page]

Professor Marko's research is focused on the question of how DNA is organized and processed inside cells. His group carries out single-DNA stretching experiments to study protein-DNA interactions and chromatin structure, as well as experiments on living cells to directly study whole chromosomes. Prof. Marko's group also uses statistical mechanics to study problems in molecular biophysics.

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Adilson E. Motter [Motter Research Page]

Professor Motter's research is focused on complex systems and nonlinear phenomena, primarily in the realm of chaos, fractals, statistical physics, complex networks, and biological physics. Current projects include whole-cell modeling of cellular metabolism, system-level approach to cascading failures in infrastructure networks, synchronization and other dynamical phenomena in complex networks, advection dynamics in chaotic fluid flows, and foundations of chaos in classical and relativistic systems.

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Sara Solla

Sara Solla's research interests lie in the application of statistical mechanics to the analysis of complex systems. Her research has led her to the study of neural networks, which are theoretical models that incorporate "fuzzy logic" and are thought to be in some aspects analogous to the way the human brain stores and processes information. She has used spin-glass models (originally developed to explain magnetism in amorphous materials) to describe associative memory, worked on a statistical description of supervised learning, investigated the emergence of generalization abilities in adaptive systems, and studied the dynamics of incremental learning algorithms. Solla has also helped develop constrained neural networks for pattern-recognition tasks, along with descriptions of the computational capabilities of neural networks and learning.

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