Beomjin Kwon, Ph.D. (kwon at asu dot edu)

Dr. Beomjin Kwon is an Associate Professor of Mechanical Engineering at Arizona State University, where he was promoted to tenure in 2025. He joined ASU in 2018 as a tenure-track Assistant Professor. His research focuses on developing artificial intelligence (AI)-driven methods for visualization, field reconstruction, and design of complex thermofluidic and energy systems.

Dr. Kwon received his Ph.D. (2013) and M.S. (2009) in Mechanical Engineering from the University of Illinois at Urbana-Champaign (UIUC). He began his professional career at the Korea Institute of Science and Technology (KIST), where he served as a Research Scientist (2013–2014) and Senior Research Scientist (2015–2016). Before joining ASU, he was a Postdoctoral Research Associate at UIUC (2017–2018).

Nagahiro Ohashi (nohashi at asu dot edu)

PhD student in Mechanical and Aerospace Engineering

Nagahiro received his BS in 2021 and MS in 2023 in mechanical engineering from the University of Hawaii at Manoa. His research interest focuses on using deep learning techniques to derive temperature distributions via a network trained with experimental data.

Hyder Bukhari (hbukhar3 at asu dot edu)

PhD student in Mechanical and Aerospace Engineering

Hyder earned his Bachelor's degree in Aerospace Engineering from the National University of Sciences and Technology (NUST), Islamabad, in 2021. After graduating, he worked in the aerospace industry for three years. His research interests focus on using deep learning techniques to visualize heat transfer and fluid mechanics, specifically leveraging these techniques to achieve visualizations unattainable with traditional measurement methods. 

Changmin Oh (changmi1 at asu dot edu)

MS student in Mechanical Engineering

Changmin is an M.S. student in Mechanical Engineering. His current research focuses on first-principles density functional theory (DFT) simulations of carbon nanotube/copper interfaces, with particular interest in interfacial charge transfer, electronic structure, and the role of molecular interface engineering in enhancing electrical conductivity.

Yeasung Kim (ykim296 at asu dot edu)

MS student in Artificial Intelligence Engineering (Mechanical Engineering)

Yeasung received his BS in Computational Mathematical Sciences from Arizona State University. His research focuses on scientific machine learning, particularly hyperparameter optimization of multiple-domain physics-informed neural networks (MDPINNs) for water–air bubble flows and the development of LLM-integrated AI agents for automated PINN modeling and optimization.

Hyeonji Sim (hyeonjis at asu dot edu)

BS student in Mechanical Engineering

Hyeonji is an undergraduate student in Mechanical Engineering at Arizona State University. Her current research focuses on particle image velocimetry (PIV) experiments to investigate the water flow surrounding a rising air bubble. She is particularly interested in experimental fluid mechanics, multiphase flows, and optical flow measurement techniques.