Jinlong Wu

Professor Jinlong Wu is a faculty member in the Department of Mechanical Engineering at the University of Wisconsin-Madison. His research focuses on developing efficient and reliable data-driven modeling and simulation techniques for complex dynamical systems, with applications in multi-scale, multi-physics, and chaotic systems. He holds a PhD from Virginia Tech (2018), an MS from Southeast University (2014), and a BS from Southeast University (2011).

• Education:
• PhD in Mechanical Engineering, Virginia Tech, 2018
• MS in Mechanical Engineering, Southeast University, 2014
• BS in Mechanical Engineering, Southeast University, 2011

His research interests include Physics-Informed Machine Learning, Bayesian Inference, Turbulence, Computational Fluid Dynamics, Climate Dynamics, and Uncertainty Quantification. He has developed frameworks like CGKN and ChronoLLM, advancing data assimilation and digital twin technologies.

Recent publications highlight contributions to stochastic closure modeling, ensemble Kalman inversion, and neural operator-based approaches for dynamical systems. His work emphasizes bridging machine learning with traditional computational methods to tackle challenges in turbulence, climate, and robotics.

• Awards:
• 2018 Paul E. Torgersen Graduate Student Research Excellence Award
• 2018 Pratt Fellowship
• 2017 SIAM Travel Award
• 2016 APS DFD Travel Award
• 2014 Pratt Fellowship

Teaching includes courses such as M E 363 (Fluid Dynamics) and M E 890 (PhD Research and Thesis). No listed advisees are available. His work aligns with interdisciplinary collaborations in computational mechanics and environmental modeling.