Hello, and welcome! I am Redowan Ahmed Niloy, a Postdoctoral Research Associate in the Department of Aerospace & Mechanical Engineering (Bioengineering) at the University of Notre Dame, working with Prof. Maria Holland.
My research asks how mechanical forces shape soft tissue, from how tissues fold during development to how they fail in disease. At Notre Dame, I build layer-resolved, nonlinear finite element models of the human appendix during acute appendicitis, link clinical biomarkers to tissue mechanics for earlier diagnosis, and apply growth mechanics to mouse brain development in collaboration with Prof. David Van Essen (Washington University in St. Louis). I also develop Bayesian physics-informed neural networks for inferring tissue mechanics from data. This work earned an Indiana CTSI (NIH) Postdoc Challenge Award.
I received my Ph.D. and M.S. in Mechanical Engineering from Texas Tech University in August 2024, advised by Prof. Jerzy Blawzdziewicz. My dissertation developed advanced vertex models that explain the cellular mechanics of cephalic furrow formation in the Drosophila embryo, published in Biophysical Journal. At Texas Tech I also served as a Graduate Instructor and Teaching Assistant and held a Doctoral Dissertation Completion Fellowship. After my Ph.D., I was a Visiting Assistant Professor at Kennesaw State University in Marietta, Georgia, where I taught Thermodynamics and Fluid Mechanics.
I earned my B.Sc. in Mechanical Engineering from Bangladesh University of Engineering & Technology (BUET), where I studied the transonic aerodynamics of airfoil cascades with Prof. A. B. M. Toufique Hasan. Before that, I attended Notre Dame College and Civil Aviation High School in Dhaka, the city where I grew up.
Outside research, I find history, art, and the development of societies fascinating, and I love to read and travel.
Email: rniloy@nd.edu
Key SkillsÂ
Research methods: Finite element analysis (nonlinear, layer-resolved soft tissue), vertex modeling, continuum growth mechanics, low-Reynolds-number hydrodynamics, physics-informed machine learning (B-PINNs).
Programming languages: Fortran, C++, Python, MATLAB, C, R, Bash.
Numerical computing environment: MATLAB, Mathematica.
Modeling and simulation: ANSYS Fluent, COMSOL.
Data plotting and visualization: Gnuplot, Tecplot, CFD-Post.
Drawing and design: SolidWorks, AutoCAD.
Operating systems: Linux, Windows.
Documentation and presentation: LaTeX, Office Suite.
Editing software: Inkscape, Adobe Illustrator, Adobe Photoshop.