Ph.D. Students

Mohammad Al-Jarrah

I am a Ph.D. student in the Department of Aeronautics and Astronautics at the University of Washington (UW), where I have been studying since January 2023. I obtained my master’s degree in 2020 from the same department. In 2018, I graduated with my undergraduate degree as the top student in my class and received the Geda and Phil Condit Endowed Fellowship for two years at UW. In 2024, I was honored with several awards, including the A&A Student Excellence Award for doctoral students, the UW SPEEA Aerospace Career Enhancement (ACE) Fellowship, the Sarchin Fellowship Award, and the Outstanding Student Paper Award at the 2024 IEEE Conference on Decision and Control (CDC) in Milan, Italy. My current research focuses on developing a novel algorithm to solve the nonlinear filtering problem. This work incorporates the theory of optimal transport and deep learning. My research goal is to establish a new framework for decision-making under uncertainty.

Yuhang Mei

I am a first-year PhD student in Aeronautics and Astronautics Department at University of Washington advised by Prof. Amir Taghvaei. Besfore joining UW, I completed my master’s in Mechanical Engineering and Electrical & Computer Engineering at University of Michigan advised by Prof. Necmiye Ozay. I obtained my Bachelor degree in Mechanical Engineering at Huazhong University of Science and Technology. My research focus on the intersection of machine learning and control.

Jenny Jin (co-advised)

I’m Niyizhen(Jenny) Jin a 1st year PhD student in Applied Math at the University of Washington. I work on problems in optimal transport with machine learning applications. My area of interests include uncertainty quantification and data science.




Michele Martino (co-advised)

I am a Ph.D. student in Applied Mathematics at the University of Washington from Rome, Italy. I received a B.S. Honors in Mathematics from the University of Rochester and I am currently working under the supervision of Professors Bamdad Hosseini and Amir Taghvaei on transport methods for conditional sampling. During the reminder of my Ph.D., I hope to deepen my research in the fascinating field of optimal transport and its many applications in machine learning, uncertainty quantification, and data science