Muralikrishnan (Murali) Gopalakrishnan Meena is a Postdoctoral Research Associate in the Advanced Computing for Life Sciences & Engineering group of the Science Engagement section. Murali’s research at ORNL involves using machine learning to formulate subgrid-scale turbulence closures for cloud resolving models.
Prior to joining ORNL, Murali obtained his Ph.D. in Mechanical Engineering from the University of California, Los Angeles in 2020. His Ph.D. research focused on using network (graph) theory to characterize, model, and control vortical interactions in turbulence and wake flows. In particular, he introduced a network community-based framework to identify closely interacting vortical elements which were used to formulate reduced-order models and perform flow-modification of complex laminar and turbulent vortical flows. He previously worked as a Graduate Research Assistant during his graduate studies at UCLA and Florida State University.
Outside of work, Murali enjoys sailing, surfing, swimming, and painting.
University of California, Los Angeles
Doctor of Philosophy (Ph.D.)
Florida State University
Master of Science (M.S.)
Cochin University of Science & Technology, India
Bachelor of Science (B.S.)
C.-A. Yeh, M. Gopalakrishnan Meena, and K. Taira, "Network broadcast mode analysis and control of turbulent flows", Journal of Fluid Mechanics, 910, A15, 2021.
M. Gopalakrishnan Meena and K. Taira, "Identifying vortical network connectors for turbulent flow modification", Journal of Fluid Mechanics, 915, A10, 2021.
Z. Bai, N. B. Erichson, M. Gopalakrishnan Meena, K. Taira, and S. L. Brunton, "Randomized methods to characterize large-scale vortical flow network", PLoS One, 14(11): e0225265, 2019.
M. Gopalakrishnan Meena, A. G. Nair, and K. Taira, "Network community-based model reduction for vortical flows", Physical Review E, 97, 063103, 2018.
M. Gopalakrishnan Meena, K. Taira, and K. Asai, "Airfoil wake modification with Gurney flap at low-Reynolds number", AIAA Journal, 56(4), 1348-1359, 2017.