• Physics informed deep learning
• Data-driven fluid synthesis
• Conditional video generation

I'm interested in physics informed deep learning for video and fluid synthesis. Currently, I am a Lise Meitner Postdoctoral Research Fellow at Max Planck Institute for Informatics, supervised by Prof. Dr. Christian Theobalt and Dr. Rhaleb Zayer. Previously, I studied as a Ph.D. student in Prof. Nils Thuerey’s group, at Technical University of Munich, from 2014 to 2020. I received my M.Eng. degree from Zhejiang University, China in March 2014.

Please find the list of my publications in the google scholar webpage .

• ***Our paper is recently accepted by SIGGRAPH 2022:***
  M. Chu, L. Liu, Q. Zheng, E. Franz, HP. Seidel, C. Theobalt, and R. Zayer. "Physics Informed Neural Fields for Smoke Reconstruction with Sparse Data", SIGGRAPH 2022
• ☛ [Project] [Code]
• ☛ [Paper] [Results]
• ☛ [Video]
• M. Chu, N. Thuerey, HP. Seidel, C. Theobalt, and R. Zayer. "Learning Meaningful Controls for Fluids", SIGGRAPH 2021
• ☛ [Project]
• ☛ [Code]
• ☛ [Video]
• M. Chu* , Y. Xie*, J. Mayer, L. Leal-Taixé and N. Thuerey. "Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation", (*Similar contributions)
• ☛ selected for Two Minutes Papers presentation
• ☛ [Project]
• Y. Xie *, E. Franz*, M. Chu* and N. Thuerey. "TempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow", SIGGRAPH 2018, (*Similar contributions)
• ☛ SIGGRAPH 2018 talk online
• ☛ [Project]
• Mengyu Chu and Nils Thuerey, "Data-Driven Synthesis of Smoke Flows with CNN-based Feature Descriptors", ACM Transactions on Graphics (SIGGRAPH Conference, 2017, Los Angeles, USA), Vol. 36, No. 4, Article 69.
• ☛ SIGGRAPH 2017 talk online, starting at 45:20
• ☛ selected for Two Minutes Papers presentation
• ☛ official TUM press release
• ☛ [Project]