People.

Current members

Principal Investigator

Ope Owoyele

Ope Owoyele has been an Assistant Professor of Mechanical Engineering at Louisiana State University since August 2021. Prior to joining LSU, he was a Postdoctoral Appointee in the Computational Multi-Physics Research Section at Argonne National Laboratory (ANL). Before that, he was an ORISE Postdoctoral Fellow conducting research at the National Energy Technology Laboratory (NETL). He received both his M.S. and Ph.D. degrees in Mechanical Engineering from North Carolina State University.

During his time at ANL, he received an Argonne Impact Award for Innovation and a Postdoctoral Performance Award in Engineering Research. His work on developing a machine learning-genetic algorithm for rapid product design optimization received an R&D 100 Award, and he is also a recipient of the Air Force Office of Scientific Research Young Investigator Program Award. His research interests lie at the intersection of scientific machine learning, numerical methods, and high-performance computing, with applications in engineering design optimization and data-driven reduced-order modeling of complex energy systems.

Postdoctoral researcher

01 member

Sattik Basu

Computational modeling of compressible and non-Newtonian biomass flows, including heat transfer, multiphase flow, and rapid phase change.

Ph.D. students

06 members

Haresh Chandrasekhar

Advanced machine learning techniques and flamelet models for turbulent reacting flows.

Okezzi Ukorigho

Scientific machine learning, reduced-order modeling, computational fluid dynamics, and turbulent combustion modeling.

Eloghosa Ikponmwoba

Reinforcement learning for swarm optimization and computational models for additive manufacturing processes.

Sourav Saha

Computational modeling of biomass dewatering processes and parametric studies for optimal operating and design conditions.

Philip John

Multi-fidelity models for sustainable aviation fuels and machine learning and flamelet modeling for turbulent reacting flows.

Ruslan Akbarzade

Biomass fast pyrolysis, multiphysics reacting flows, reduced-order modeling, and physics-informed machine learning.

Undergraduate researchers

02 members

Robert Michelsen

Computational high-fidelity modeling for capturing CO₂ release, leakage, and rupture from pipelines.

Brandon Turner

Machine learning and reduced-order models for reacting-flow applications.