Biopolymers (flexible rods), biomembranes (fluid sheets like soap bubbles), and biomolecular bonds are the Lego blocks of cells, used repeatedly inside cells to build a variety of nanometer-sized machines that help perform functions, like allowing cells to divide, crawl, organize their interiors, sense their environment and communicate with other cells.

The mission of our research group is to make rigorous, relevant contributions to the scientific knowledge of humanity. We use computational, mathematical and biophysical approaches to figure out how living cells use force, space and time in their problem-solving strategies. We work so that the basic science discoveries we make become part of the worldwide, multi-generational tapestry of scientific knowledge that benefits all.

Our approach combines mathematics, physics, and biology to tackle fundamental questions about cellular function. We develop novel computational methods and theoretical frameworks to understand how molecular interactions give rise to emergent cellular behaviors. The complexity of biological systems requires sophisticated mathematical tools, from differential equations and stochastic processes to network theory and statistical mechanics.

Each biological process we study involves intricate networks of molecular interactions operating across multiple timescales. From millisecond conformational changes in individual proteins to hours-long cell division cycles, we develop models that capture the essential physics while remaining computationally tractable. This multi-scale perspective is crucial for understanding how molecular details influence cellular outcomes.

Our research combines theoretical modeling with computational simulation to understand how biological systems achieve remarkable precision and efficiency at the molecular scale. We investigate how cells process information through molecular interactions, how they generate forces for movement and division, and how they organize complex structures in space and time.

Recent advances in computational biology and high-performance computing have opened new frontiers in understanding cellular mechanics. We leverage these tools to probe the fundamental principles governing how cells achieve their remarkable feats of organization and function. Our work bridges multiple disciplines, from statistical mechanics and stochastic processes to cell biology and biochemistry, creating a unified framework for understanding life at the molecular level.

At the heart of our approach is the recognition that cellular systems operate far from equilibrium, constantly consuming energy to maintain organization and respond to environmental changes. This perspective drives our development of novel theoretical tools and computational methods specifically designed to capture the non-equilibrium dynamics of living systems.

Understanding cellular function requires modeling across spatial scales from nanometers to micrometers and temporal scales from microseconds to hours. We develop coarse-grained models that preserve essential physical principles while enabling efficient computation of cellular-scale phenomena. These models often reveal surprising connections between molecular properties and emergent cellular behaviors.

Collaboration is central to our research philosophy. We work closely with experimental biologists to ensure our models are grounded in biological reality and can make testable predictions. This iterative process of modeling, prediction, and experimental validation drives scientific discovery and advances our fundamental understanding of life.

The biological functions we work on include how immune cells read antigen and process information signals using immuno-receptors, how the cell’s internal skeleton is built using formins, how cells in tissues communicate at long distance using airinemes.

Through interdisciplinary collaboration and innovative computational approaches, we strive to bridge the gap between molecular mechanisms and cellular behaviors. Our work spans multiple scales from individual molecules to whole-cell dynamics, integrating experimental observations with theoretical frameworks.