Hubert’s research interest is mainly in generative models and neural architecture search, he is also interested in controllable and explanable machine learning. He believes that the generative model is one of the key components to visualize and empirically prove that the machine intelligence can fully understand the data and the implicit meanings behind the scene. In the meanwhile, neural architecture search is the key-stone to fully-automated model design, which will be the next break-through in deep learning. The two long-term research goals of Hubert is:
Hubert is also looking for visiting opportunities and Ph.D. position in 2020.
Bachelor in Computer Science, 2018
National Tsing Hua University