Bhargav Sriram Siddani

Postdoctoral Scholar, Applied Mathematics and Computational Research Division

Contact Information

MS 50A-3111
Lawrence Berkeley National Lab
1 Cyclotron Rd.
Berkeley, CA 94720

[email protected]

Google Scholar, ORCiD

I am a postdoctoral scholar in the Center for Computational Sciences and Engineering (CCSE) in the Computing Sciences Area at the Lawrence Berkeley National Laboratory.

My research background is in particle-laden multiphase flows and data-driven modeling for these flow applications. I am currently involved in the development of multiscale framework for Complex Fluids and Multiphase Flow and data-driven model development and integration into this framework. My research interests include computational multiphase flows, scientific machine learning for fluid mechanics, and high performance scientific computing.

I obtained my Ph.D.(2022) and M.S.(2019) in Mechanical Engineering from the University of Florida, and B.Tech.(2017) in Mechanical Engineering from National Institute of Technology Karnataka, India. Upon graduation I worked as a postdoctoral scholar(2023) with the NETL MFS group.

Recent Publications

  1. Siddani, B., Balachandar, S., Zhou, J., & Subramaniam, S. (2024). Investigating the influence of particle distribution on force and torque statistics using hierarchical machine learning. AIChE Journal, e18339.
  2. Siddani, B., & Balachandar, S. (2023). Point-particle drag, lift, and torque closure models using machine learning: Hierarchical approach and interpretability. Physical Review Fluids, 8(1), 014303.
  3. Siddani, B., Balachandar, S., Moore, W. C., Yang, Y., & Fang, R. (2021). Machine learning for physics-informed generation of dispersed multiphase flow using generative adversarial networks. Theoretical and Computational Fluid Dynamics, 35, 807-830.
  4. Siddani, B., Balachandar, S., & Fang, R. (2021). Rotational and reflectional equivariant convolutional neural network for data-limited applications: Multiphase flow demonstration. Physics of Fluids, 33(10).