Assistant Professor

Biography

Prof. Chen received his Bachelor degrees from Tsinghua University in 2016, followed by a Diplôme d'Ingénieur and a PhD from Mines Paris – Université PSL. From 2022 to 2025, he was a postdoctoral researcher at Southern University of Science and Technology.

Research Interests

Reliable, efficient, and robust deep-learning methods for computational science and engineering; data-driven flow modeling; multiscale and chaotic dynamics; dimension reduction and reduced-order modeling.

Teaching

• MATH2411  Applied Statistics

Selected Publications

  Article

1. Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning
   • Author(s): Chen, Junfeng; Wu, Kailiang
   • Source: Proceedings of Machine Learning Research, v. 235, p. 7526-7552, article number 293
   • Year: 2024


2. A twin-decoder structure for incompressible laminar flow reconstruction with uncertainty estimation around 2D obstacles
   • Author(s): Chen, J.; Viquerat, J.; Heymes, F.; Hachem, E.
   • Source: Neural Computing and Applications, v. 34, (8), p. 6289-6305
   • Year: 2022


3. Graph neural networks for laminar flow prediction around random two-dimensional shapes
   • Author(s): Chen, J.; Hachem, E.; Viquerat, J.
   • Source: Physics of Fluids, v. 33, (12), article number 123607
   • Year: 2021