Research
Intelligent representations of matter for science-grounded AI, first-principles modeling, multiscale simulation, and useful materials discovery.
Open researchHow Matter Meets Intelligence
We develop science-grounded AI and physical simulation frameworks that represent matter in forms human and artificial intelligence can reason with: structure, symmetry, thermodynamics, kinetics, uncertainty, and design feasibility.
Xie Lab studies how matter should be represented so that scientific intelligence can reason about mechanisms, explore design spaces, and steer the discovery and making of useful materials.
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We combine materials physics, multiscale simulations, and science-grounded AI to build representations that make complex materials systems easier to understand, design and make.
Intelligent representations of matter for science-grounded AI, first-principles modeling, multiscale simulation, and useful materials discovery.
Open researchCourses and mentoring that connect physical reasoning, mathematical structure, and reproducible computational practice.
Open teachingCurrent students, alumni, undergraduate mentoring, and group photos from recent lab activities.
Meet the groupSelected recent papers, code and data links, and the complete Google Scholar publication record.
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The complete and most current publication list is maintained on Google Scholar.
Open publications page2026
Yiheng Shen, Chang Liu, Wei Xie*, and Wei Ren*. The Journal of Physical Chemistry Letters, 17(12), 3492-3498.
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Prospective graduate students, visiting students, and collaborators may contact the lab with a short research statement, CV, and representative work.
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