Weishi Shi

Assistant Professor, University of North Texas

Dr. Weishi's research studies how to implement various learning strategies to make machine learning data efficient, which means reducing the human annotation costs at different phases of machine learning, including model training, model testing, and model validation. He mainly develops active learning algorithms for other machine learning tasks and models.


  • Bayesian Optimization
  • Machine Learning
  • Active Learning
  • Pattern Recognition