Our mission is to develop quantitative measurement frameworks that redefine how complex biological systems are studied and enable predictive understanding of their behavior. Biological systems are inherently complex, composed of heterogeneous components interacting across multiple spatial and temporal scales. Advances in measurement technologies and high-performance computation now allow us to observe biological systems with unprecedented depth and scale. The central challenge is no longer data acquisition alone, but determining how to design measurements, interpret high-dimensional observations, and connect molecular processes to collective biological function.

The Han Lab develops experimental and theoretical tools that make previously unobservable dimensions of biological organization measurable. By integrating chemistry, bioimaging, microfluidics, and advanced analytics, we build platforms that expand the experimental boundaries of modern biology. Our work often begins by asking what aspects of biological organization are not well captured by existing measurement approaches. Addressing these gaps may require new measurement strategies, new analytical frameworks, or both. We therefore develop experimental platforms and analytical methods in parallel so that they inform one another as our understanding of the system evolves.

Although the biological systems we study span a wide range of scales, from viruses to cellular membranes to whole brains, they share common features: heterogeneity, multiscale organization, and strong interactions among components. These are precisely the regimes where new measurements can reveal organizational principles inaccessible to conventional approaches.

Our flagship research programs:
1) Single Virus Genomics and Influenza Evolution
2) Spatial Omics for Systems-Level Brain Function
3) Membrane Protein Signaling in Membrane Environments

illustrate this measurement-driven approach to understanding complex biological systems. Our lab brings together researchers from chemistry, engineering, physics, and biology who share an interest in developing new ways to measure and understand complex biological systems.