Hello, I'm
Qian-Ze Zhu
PhD Candidate at Harvard University exploring nonequilibrium self-organization and molecular computing through statistical physics, differentiable simulation, and machine learning.
About Me
I am a 5th-year PhD student in Applied Physics at Harvard University, studying how computation, learning, and organization emerge in complex systems far from equilibrium. I am fortunate to be advised by Prof. Michael P. Brenner.
My research combines statistical physics, differentiable simulation and machine learning to uncover fundamental limits and design principles governing self-assembly, information flow, and molecular computation.
Learn More About Me →Research Interests
Exploring the boundaries between physics, computation, and biology
Nonequilibrium Self-Organization
Exploring how nonequilibrium driving and energy dissipation can steer robust self-assembly through mechanisms such as proofreading, error correction, and state change, enabling high-yield assembly beyond equilibrium limits.
Molecular Computing
Studying how computation can be embedded in molecular dynamics, where tailored interactions and nonequilibrium kinetics guide physical and biological systems toward solutions of hard combinatorial problems.
Differentiable Simulation
Developing end-to-end differentiable molecular dynamics and stochastic simulations to enable inverse design and optimization of stochastic physical and biological systems, especially far from equilibrium.
Computational Biology
Modeling biological information processing, from gene regulatory networks to neural systems, using stochastic and physics-based computational frameworks.
AI for Science
Developing AI systems that leverage large language models and search to automate scientific modeling, accelerate discovery, and build generalizable computational tools for physics and biology.
Beyond Research
Capturing moments from travels around the world
