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Intelligent Matter Lab

What if active materials can learn? Living systems assemble, adapt, and generate function through the interactions of many parts. We ask how those principles can become a foundation for a new kind of physical system.

Our long-term vision is intelligent matter: collections of simple physical units whose local rules enable the whole to sense, reorganize, and act. We approach that vision through experiments in living matter, programmable robotic systems, and learning.

We discover how local, nonreciprocal interactions generate new collective dynamics and states of matter.

We investigate how local rules can be learned and how physical interactions and material states can encode memory.

We seek to understand how distributed sensing, learning, and information exchange can produce adaptable collective functions.

The possibility is a new approach to embodied intelligence: complex collective functions arising from learned interactions among many simple physical units. If these principles generalize, they could provide a foundation for adaptable robotic swarms, reconfigurable machines, and eventually intelligent materials.

01 / ROBOTIC MATTER

Physics of Emergence

How do simple local interactions give rise to complex collective behaviors? We investigate the fundamental physical principles governing self-organization, collective dynamics, and emergent properties in active matter.

[ Learn more | preprint ]

Learning & Memory

Can physical matter learn, remember, and adapt through its own interactions? We combine statistical physics and machine learning to uncover how collective systems can acquire new functions and encode memories in their physical dynamics.

[ Learn more ]

Information-driven organization

Can interacting physical systems become a substrate for collective intelligence? We explore how information exchange, distributed decision-making, and embodied AI can transform robotic swarms into intelligent, adaptive collectives.

[ Learn more ]

02 / LIVING MATTER

Morphological Manifold

How can biological shape reveal cell identity, developmental states, and trajectories? We combine machine learning and symmetry analysis to uncover how cell and tissue morphology encode biological states and evolve during development.

[ Learn more | Review ]

Nonreciprocal living & active matter

Living systems are full of interactions that break action-reaction symmetry, from ciliary flows to chiral tissues. We study how nonreciprocal interactions generate collective motion, odd mechanical response and emergent organization in living matter.

[ Learn more | nature ]

Chiral Morphogenesis

How does chirality emerge and break left-right symmetry during development? We study sea star embryos to uncover the physical mechanisms driving chiral morphogenesis.

[ Learn more | PRX Life ]

Principal Investigator

Tzer Han Tan is an Assistant Professor of Physics at UC San Diego. He leads a research lab developing living and synthetic active matter systems to better understand physical principles that underlie complexity in collective behavior. Before joining UC San Diego, he was a ELBE Postdoctoral Fellow at the Max Planck Institute for Physics of Complex Systems. Tzer Han received his Ph.D. in Physics at MIT and his B.S. in Applied and Engineering Physics at Cornell University. Tzer Han's awards include the William A. Lee Chancellor's Endowed Junior Faculty Fellowship, Hellman Fellowship and the DOE Early Career Award.

News

Oct 2026: Tzer Han has been awarded a DOE Early Career Award to study physical learning in nonreciprocal active matter. Very honored!

Sep 2026: Andrew Truttman has been selected as a NIH T32 student fellow to study mechanisms of mitotic waves. Congrats Andrew!

May 2026: Tzer Han has received a NIH MIRA (R35) Award to study morphological landscape to define cell states and cell types using representation learning.

Mar 2026: Ouyang Xuan has been selected as a Keck Student Fellow to study morphological landscape of tissues. Congrats Xuan!

Feb 2026: Tzer Han has received a DARPA Defense Science Office (DSO) Pitch Day award! With co-PI Prof. Gravish and Prof. Boechler, they will develop robotic swarms as programmable states of matter.

Aug 2025: Shiqi Liu joins the lab, working on physical learning in nonreciprocal robotic matter. Welcome Shiqi!

July 2025: Tzer Han has been selected as UCSD Hellman Fellows. Congratulations!

team members

Fan Bo

Postdoctoral Fellow

Shiqi Liu

Postdoctoral Fellow

Wyatt Joyce

PhD student

Gregor Leech

PhD Student

Ouyang Xuan

PhD student

Andrew Truttman

PhD student

Undergraduate Students

Zenghong He (Electrical Engineering, Class of 2026)
Hrithik Yash (Mechanical Engineering, Class of 2027)
Eyad Alqatari (Physics, Class of 2028)
Feiyi Ruan (Computer Science)
Haruhiko Akimoto (Physics, Class of 2027)
Jeremy Lin (Electrical Engineering, Class of 2027)
Logan Wong (Electrical Engineering, Class of 2027)

Alumni

Yutao Deng (currently Masters at CMU)
Zeyu Qi (soon Masters at Columbia U)

our team is recruiting

We are looking for motivated and creative undergraduate/PhD/postdocs to join our team!

In particular, the active research directions in the lab are:

Chiral active matter, with a focus on phase transitions, the role of disorder and collective dynamics using marine invertebrate embryos (e.g. P. miniata, Platynereis) as model
Nonreciprocal robotic active matter, with a focus on designing odd elasticity, nonreciprocal phase transiton and active learning using our newly developed p-atic robotic active matter.
Chiral morphogenesis, with a focus on chiral symmetry breaking in marine embryos, morphological landscape of organoids, optogenetics, tissue mechanics and mechanochemical coupling

Our lab is primarily an experimental soft matter/biophysics lab with plenty of opportunities to collaborate with theory groups. We aim to combine experiments with creative data analysis to understand how symmetry, order and dynamics emerge in living matter.

Postdocs. Please email Tzer Han directly with CV and a short statement of interest. We welcome applicants from diverse and international background.

PhD and undergraduate students. Students already at UCSD can contact Tzer Han directly. Otherwise, you can apply to the Physics PhD program here. Deadline Dec 18, 2026.