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Current openings:

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I am actively seeking highly motivated Ph.D. students (fully sponsored) and research interns (non-paid) with a strong foundation in probability, linear algebra, and/or optimization and solid programming skills to join my research group in the Department of Computer Science at Florida State University. Our group focuses on advancing the interdisciplinary studies of machine learning and scientific computing, contributing to the reciprocal relationship between these fields.

My main research focus include:

  • Probabilistic Machine Learning: Bayesian machine learning and modeling, approximate inference
  • ML for Scientific Computing: surrogate modeling, operator learning, physics-informed machine learning
  • Multi-Objective ML: multi-task learning, meta-learning, transfer learning
  • Interactive Machine Learning: active learning, Bayesian optimization, bandits, reinforcement learning

Before joining FSU, I obtained my Ph.D. degree from the School of Computing at the University of Utah. I received my M.S. degree from the University of Pittsburgh and my B.E. degree from South China University of Technology.

Requirements (for Ph.D. applicants):

  • GPA ≥ 3.5/4.0
  • TOEFL > 80 for international students (speaking ≥ 23 desired)
  • Background in Computer Science, Mathematics, Physics, Statistics, and ECE is preferred.
  • Programming experience
  • Familiar with modern machine learning frameworks is preferred such as TensorFlow, PyTorch, Jax.

Application Package (for Ph.D. applicants):

  • Curriculum Vitae/Resume
  • Statement of Purpose
  • Official transcripts with GPA
  • GRE test results
  • Three letters of recommendation
  • TOEFL or IELTS scores for international students

How to Apply: