Hi, this is JJ (朱家傑). I studied mathematics for my undergraduate degree at Fudan University in Shanghai. Following that, I received doctoral training in numerical analysis and optimization during my Ph.D. study guided by William Hager at the University of Florida. After moving to Europe and being awarded the Marie Curie Individual Fellowship, I learned numerical methods for robust nonlinear optimization and control from Moritz Diehl during a research stay at the University of Freiburg. Recently, I was a postdoctoral researcher in machine learning at the Empirical Inference Department, Max Planck Institute for Intelligent Systems in Tübingen, Germany, where I worked on the theory of kernel methods, and robustness for machine learning. Recently and since moving to Berlin, I learned the theory of gradient flows of (probability) measures in the optimal transport geometry from Alexander Mielke. In my spare time, I enjoy science fiction and playing sports.

Here (in both German and English) is a previous journal interview about my career path. There is also a previous article in a magazine interview.