Team

Principal Investigator


Ehsan Madadi

Assistant Professor, Mechanical and Aerospace Engineering Department

Education:

  • Ph.D., Mechanical Engineering, Iowa State University, 2017
  • M.Sc., Mechanical Engineering, University of Tabriz, 2011

Professional Experience:

  • Postdoctoral Research Associate at the Department of Petroleum and Geosystem Engineering, the University of Texas at Austin
  • Postdoctoral Research Associate at National Center for Infrastructure Modeling and Management, the University of Texas at Austin

Research Interests:

  • Multiphase fluid dynamics
  • Computational fluid dynamics (CFD)
  • Turbulent mixing and reacting flows
  • Numerical methods
  • Complex fluids
  • Development of open-source tools for CFD

Bio:

Ehsan Madadi is an assistant professor of the Department of Mechanical and Aerospace Engineering at California State University, Long Beach. His research focuses on the development, implementation, and validation of accurate and tractable computational fluid dynamics (CFD) tools for multiphase and turbulent flows, and environmental fluid modeling. He has generated new computational algorithms that improve our ability to model complex physical processes of fluid flow and transport for computational modeling of multiphase, turbulent mixing, and reacting flows.

Before joining CSULB, he was a Postdoctoral Fellow (2017-2020) at the Department of Petroleum and Geosystems Engineering (2020), and the Center for Water and the Environment (2017-2020) at the University of Texas at Austin, where he contributed to several nationally funded projects in collaboration with the United States Environmental Protection Agency and United States Department of Energy. He received his Ph.D. in Mechanical Engineering from Iowa State University in 2017, with a focus on quadrature-based models for multiphase and turbulent reacting flows.

Graduate Students


Elizabeth Alvarez

Education: M.Sc., Mechanical Engineering at CSULB (Fall 2024)

Research Focus: Mixing and its applications.

Brandon Hubbard

Education: M.Sc., Aerospace Engineering at CSULB (Spring 2025)

Research Focus: Premixed flames.

Michael Truong

Education: M.Sc., Mechanical Engineering at CSULB (Spring 2025)

Research Focus: Dilute gas simulations

Undergraduate Students


Ailar Naghshineh

Education: B.Sc., Aerospace Engineering at CSULB (Spring 2024)

Alumni


Graduate Students

Andrew Gonzalez, M.Sc. Mechanical and Aerospace Engineering, May 2022. Thesis: Computational study on the flame and extinction behavior of a high enthalpy air slab. First employment: Virgin Galactic.

Anthony Cervantes, M.Sc. Mechanical Engineering, December 2022.

Undergraduate Students

Thomas Nguyen, B.Sc. Aerospace Engineering, May 2022. Thesis: Application of RANS closure on modeling of Multi-inlet vortex reactor. First employment: Millennium Space Systems.

Alex Aubertin, B.S., Mechanical Engineering, January 2024.

Denver Davis, B.S., Mechanical Engineering, January 2024.

Sindi Ascencio Barrera, B.S., Aerospace Engineering, August 2023.

Nickey Diorio, B.S., Aerospace Engineering, August 2023.

Jessica Rogado, B.S., Mechanical Engineering and B.A. in Physics, May 2022. First employment: Rivian Automotive.

Aaron Gutierrez, B.S., Aerospace Engineering, December 2022.

Phillip Ho, B.S., Mechanical Engineering, December 2022. First employment: Puget Sound Naval Shipyard.

Visiting Scholar

Haroun Naina, B.Sc. Mechanical Engineering, August 2022. Thesis: Investigation on turbulence model for multi-inlet vortex reactor transient simulation. First employment: Graduate Student at EPFL Switzerland.

Positions


To be eligible to join our lab, students must first be admitted into the program at the California State University, Long Beach, typically in the graduate fields of Mechanical and Aerospace Engineering (though other fields will also be considered). Information on the Mechanical and Aerospace Engineering program can be found here.

While interested candidates not yet admitted to the CSULB graduate program are welcome to contact Prof. Madadi by email, note that an answer is unlikely due to the large number of solicitations.