Tomoki Koike


Greetings, and welcome to my personal website. I am currently pursuing dual academic paths, working towards both a Ph.D. in aerospace engineering and an M.S. degree in computational science and engineering at Georgia Institute of Technology. Here, I have the privilege of collaborating with Dr. Elizabeth Qian as a dedicated member of the pioneering ACE Lab. My academic journey has been shaped by a diverse range of experiences, beginning with my upbringing in Detroit, Michigan and Shizuoka, Japan, and culminating in my undergraduate education at Purdue University West Lafayette, where I cultivated a strong foundation in aerospace engineering.

My primary research interests lie at the intersection of aerospace engineering and compuational methods. I am committed to exploring and advancing the fields of model reduction, control systems, and scientific machine learning. I am interested in methods such as Operator Inference, Lift & Learn, Physics-Informed Neural Networks (PINNs), Koopman theory, and DeepONet, all while delving into the other fields of network information systems and multiagent systems.

One of my core projects centers around addressing the unique challenges posed by extreme data conditions. Whether dealing with exceptionally large datasets or highly randomized and dispersed data, my work focuses on pioneering model reduction methods that harness the latest advancements in technology. By leveraging state-of-the-art techniques, I aim to develop novel approaches that allow for efficient and effective modeling in these challenging scenarios, ultimately contributing to the cutting-edge research landscape.

Thank you for visiting, and I look forward to sharing my journey and insights with you.