Meet Dr. Yueyang Shen, a DCMB recent PhD graduate

Thursday, May 15, 2025, Yueyang Shen defended his Ph.D. dissertation titled “Complex time representation and observability of repeated measurement processes with applications of spacekime analytics.” His mentor was professor Ivo Dinov.

Shen brings together concepts from mathematics, physics and statistics, and applies these intuitions to neuroimaging to understand brain activity. Specifically, Shen has worked on physical spatiotemporal processes (for waves, and the most general case, our universe) modeled by partial differential equations. Later on, he worked on numerical and statistical techniques that resemble and augment time series representations. He then explored principles for making neural networks effective under physical constraints (symmetry) and applied these principles to spatiotemporal functional magnetic resonance imaging (fMRI) data of the brain (neuroimaging) that measures the small changes in blood flow that occur with brain activity.

To validate his model, he interrogated a dataset of five subjects whose brain activity was recorded using fMRI while listening to different music genres. His machine learning model accurately predicted the type of musical stimulus between 25% to 35% (averaged: 28.5%) of the cases. These preliminary findings are very encouraging. 

These results took about six months to come about, and “it was exhilarating to see one attempt that finally worked for predicting the music genre from brain fMRI responses. The theoretical foundations that I had worked on in my previous theory-driven papers had eventually materialized into some exciting applications!” he said.

Shen has been interested in developing and applying mathematics and statistics for a long time, and first as an electrical engineer. He then explored string theory and quantum gravitational attempts to bridge general relativity with quantum mechanics, which stems from his first PhD research project on Wheeler Dewitt equation, a model that encodes the universe's evolution. Later on in his PhD, he turned to neuroimaging, where similarly as in physics, dynamics are observed and displayed in space-time. 

“I've had the privilege of working with Yueyang Shen as his dissertation advisor over the past few years. The contributions of his doctoral research transcend the domains of mathematical-physics, computational-statistics, bioinformatics and augmented intelligence. The blend of Yueyang’s theoretical, experimental, and applied spacekime analytics is likely to have a broad and lasting impact on future scientific discoveries. We're excited to see where his career leads and are committed to supporting his continued growth as both an academic scholar and a highly skilled professional.”—Ivo D. Dinov, Henry Philip Tappan Collegiate Professor, Statistics Online Computational Resource, SPL, HBCS, DCMB, MCAIM, BIDS-TP

Shen is particularly interested in the interdisciplinary nature and the breadth of the content he works on: “I am constantly learning and exposed to new things every day,” he said. “Interdisciplinary work gives me the premier opportunity to learn, collaborate and present work to really smart people: mathematicians, physicists, statisticians, neuroscientists and bioinformaticians and data scientists. All these practitioners take very different approaches to modeling and are all tackling very hard and interesting problems that often bear synergies.”

He expresses great gratitude for his mentor, professor Ivo Dinov. In his own words: “I owe a lot to my advisor professor Dinov whose patience and kindness have been essential for me throughout my doctoral studies. His gentle mentorship helped shape my professional growth, my worldview, and the scientific principles I hold dear. I benefited much from the freedom and support he gave me to explore a spectrum of research directions. His interdisciplinary expertise, deep insights, and meticulous work ethics set a role model for me and helped me carve out this dissertation, grow as a bio-STEM researcher, and mature as a responsible global citizen. I’m also grateful for the SOCR resources, and the many opportunities I have had to engage with a rich scientific network of extraordinary scholars through conferences, summer schools, internships, and processional events.”

Shen graduated from Michigan’s Data Science Program summa cum laude. He has been recognized with several awards, including a Best Paper Award from the ASA SMI conference (Theory & Methods, 2024). He was an IHPI Fellow, (2022), and received a Multidisciplinary Design Project High Impact Fellowship from U-M (2020) and an Outstanding Excellence Scholarship of SJTU (2018). He won the Bronze Medal at the national Chinese Mathematical Olympiad (CMO), Changsha (2016), and placed 4th in the Provincial Chinese Mathematical Olympiad. 

Following his graduation, Shen will join Wells Fargo where he already did two internships. As a quantitative analyst in a two-year rotation program, he will be working on generative AI applications and explore different aspects of financial modeling. He believes that the freedom and flexibility he had to explore a variety of courses and topics at U-M prepared him well for this new role. He looks forward to further developing his mathematical and modeling skills, now applied to a different context.

When asked, Shen gave several pieces of advice for prospective students: “Show up, do the work, effectively communicate, be open-minded and keep trying.” He also recommends learning how to leverage AI in research to increase productivity.

Outside the lab, Shen enjoys playing Sheng Ji, a game that involves quantifying risk and reward while consistently and adaptively updating strategies from observed card tiles. The game requires you to remember all the played cards from different players to rule out possibilities as well as taking one’s own risk. “It is a good mental exercise aside from research.”

Yueyang Shen, Ph.D., personal website
Yueyang Shen, Ph.D., on the Statistics Online Computational Resource (SOCR) website

Yueyang Shen visits the birthplace of KFC in Corbin, Kentucky.