GROUP INTRODUCTION

  The Zhao group started in 2016, aiming to develop an interdisciplinary approach to building general physics-based AI methods. The research lab brought together new ideas and advances in condensed matter physics, soft matter physics, and biophysics challenges.

  In 2023, we introduced DRPScore, the first deep learning-based RNA-protein scoring function for complex prediction. Our rigorous testing and analysis have proven that DRPScore outperforms all existing methods. Another success is the development of RNet, an interpretable machine learning-based network approach that acquires precise binding sites and binding dynamical behavior information. The benchmark testing results demonstrate that RNet is highly accurate and robust for RNA drug design.

  Our research interests center around fundamental structure-function principles, providing valuable insights to the scientific community. Our research interests focus on (1) fundamental principles underlying molecular structure and function; (2) encoding the principles for biomolecule design related to human diseases; and (3) developing the computational tools to address challenges in health and technology. More information about our research interests can be found here.

  We always seek talented, enthusiastic, diverse students to join our group. We believe that diversity fosters creativity and innovation, and we value each individual's unique perspectives and experiences. If you are interested in our work, we encourage you to click here to contact us.