ChE Seminar: Dr. Michael D. Graham

Event Date: February 26, 2026
Speaker: Michael D. Graham
Speaker Affiliation: University of Wisconsin-Madison
Time: 3:00-4:15 p.m.
Location: FRNY G140
Contact Name: Joshua Gonzalez
Contact Phone: 765-494-4365
Contact Email: jgonzal@purdue.edu
Open To: Attendance required for ChE PhD students
Priority: No
School or Program: Chemical Engineering
College Calendar: Show
Dr. Michael D. Graham
Steenbock Professor of Engineering
Department of Chemical and Biological Engineering,
Department of Mechanical Engineering,
University of Wisconsin-Madison
 
Host:  Dr. Osman Basaran
 
 

Bio:

Professor Michael D. Graham is the Steenbock Professor of Engineering in the Department of Chemical and Biological Engineering at the University of Wisconsin-Madison, and is also a Professor of Mechanical Engineering. He received his B.S. in Chemical Engineering from the University of Dayton in 1986 and his PhD. from Cornell University in 1992. After postdoctoral appointments at Houston and Princeton, he joined the faculty at Madison in 1994.

Professor Graham’s research interests include the dynamic of complex fluids, blood flow, and instability and turbulence in flows of Newtonian and complex fluids. He is author of two textbooks: Microhydrodynamics, Brownian Motion, and Complex Fluids and Modeling and Analysis Principles for Chemical and Biological Engineers (with James B. Rawlings).

Among Professor Graham’s professional distinctions are the François Frenkiel Award (2004) and Stanley Corrsin Award (2015) from the American Physical Society Division of Fluid Dynamics, a 2018 Vannevar Bush Faculty Fellowship from the US Department of Defense, and the inaugural William R. Schowalter Lectureship at the 2019 AIChE Annual Meeting.  In 2024 he was awarded the Eugene C. Bingham Medal of the Society of Rheology.

Professor Graham has served as an Associate Editor of the Journal of Fluid Mechanics and as Editor-in-Chief of the Journal of Non-Newtonian Fluid Mechanics.  He is Past President of the Society of Rheology.

"Data-Driven and Physics-Aware Microstructural Modeling of Flowing Complex Fluids"

Abstract:

Flows used to process complex soft materials almost always involve nontrivial deformations that cannot be captured in a rheometer but may profoundly influence the final microstructure and performance of the material.  Furthermore, accurate first-principles models to relate flow, microstructure, and stress are unavailable for most complex fluids, especially when undergoing complex deformations. We describe a framework that uses machine learning and data assimilation to circumvent these limitations, exploiting a new experimental approach from the research group of Matt Helgeson that yields microstructural information in complex flows of complex fluids. The framework is constructed to automatically satisfy the key symmetry of microstructural evolution, material frame indifference, and enables data-driven determination of microstructural evolution equations for complex fluids in very general flows. Finally, we describe a framework that combines velocimetry and spatially resolved scattering or other microstructural data to simultaneously infer the deviatoric stress in the fluid and the relationship between it and the microstructure.