Complex Systems and Biophysics

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.

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.

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.

David Schwab
Prof. Schwab works in the area of biological physics, focusing on applications of statistical physics and nonlinear dynamics to problems in biology. Some of his current interests include how computations such as memory and attention are performed by networks of neurons, how cellular populations communicate and coordinate their behavior during development, how neural systems encode stimuli efficiently and implement error correction in the face of noise, and the role of spatial structure in evolution.

To approach these questions, Prof. Schwab employs a diverse set of analytical and computational tools including statistical mechanics, dynamical systems theory, machine learning, and information theory. Furthermore, he collaborates closely with experimental colleagues working on a variety of systems ranging from the social amoebae Dictyostelium discoideum to retinal ganglion cell processing of visual input. Among the products of these partnerships is the design of novel experiments and the creation of innovative data analysis methods.

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 learnin