Jiangce Chen
Research Engineer at New York University, NY, USA.

I am a research engineer at New York University. My advisors are Nikhil Gupta and Ramesh Karri.
I obtained my PhD degree from University of Connecticut. My PhD advisor is Horea T. Ilies. I was a postdoc at Carnegie Mellon University (Jan. 2023-Jan. 2025), advised by Christopher McComb and Sneha Prabha Narra.
Research interests
My research focuses on developing a cyber-physical system that integrates the design, simulations, and manufacturing control enhanced by machine learning for additive manufacturing (AM). It aims to solve the two largest challenges faced by current AM technologies: inaccurate quality control and outdated design frameworks. This system features a real-time digital twin to improve manufacturing quality and a design optimization framework to unlock the full potential of AM in creating structures with multi-scale properties for multi-physic purpose.
News
2025
February
- My paper “Multi-Lattice Topology Optimization Via Generative Lattice Modeling” has been published at Journal of Mechanical Design.
2024
October
- My paper “Data-driven inpainting for full-part temperature monitoring in additive manufacturing” has been published at Journal of Manufacturing Systems.
August
- I presented my paper “Multi-lattice topology optimization with lattice representation learned by generative models” at IDETC/CIE 2024, DC, USA.
May
- My paper “Capturing Local Temperature Evolution during Additive Manufacturing through Fourier Neural Operators” has been published at Journal of Manufacturing Science and Engineering.
2023
August
- I presented my paper “Capturing Local Temperature Evolution during Additive Manufacturing through Fourier Neural Operators” at IDETC/CIE 2023, Boston MA, USA.
- I presented my paper “Toward Post-Superficial Temperature Monitoring During Additive Manufacturing through Data-Driven Inpainting” at 2023 Annual International Solid Freeform Fabrication Symposium, Austin TX, USA.