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Welcome to the website for UC Collaborative for AI-enabled Materials Exploration and Optimization (UC-CAMEO).

Jul 2024: Our paper, “Ab initio uncertainty quantification in scattering analysis of microscopy” has been accepted in Physical Review E.
May 2024: The preprint, “Universal Phase Identification of Block Copolymers from Physics-informed Machine Learning” is abailable on ChemRxiv.
Sep 2023: Our paper, “Probabilistic forecast of nonlinear dynamical systems with uncertainty quantification” has been accepted in Physica D: Nonlinear Phenomena for publication.
Aug 2023: Our paper, “Beyond nature’s base pairs: machine learning-enabled design of DNA-stabilized silver nanoclusters”, is accepted in Chemical Communications for publication.
Jul 2023: We organized the joint workshop of UC Collaborative for AI-enabled Materials Exploration and Optimization (UC-CAMEO) and Collaboration Strengthening through Data Science (CSDS) for 20 participants from 4 UC campuses on July 17-18. Here is the agenda of the workshop.
Jul 2023: Our paper, “Data-Driven Model Construction for Anisotropic Dynamics of Active Matter”, is accepted in Physical Review X Life for publication.