EBM Seminar Talk: Harnessing AI/Data-Empowered Computational Models to Brain Mechanics and Nano-Biomaterial Interface, Xianqiao (XQ) Wang (College of Engineering, University of Georgia, USA )

Abstract: Biomechanics research faces significant challenges in addressing the inherent complexity of biological systems and the limitations of experimental approaches in capturing multiscale phenomena. AI and data-empowered computational mechanics have emerged as powerful tools, bridging gaps in spatiotemporal resolution and enabling predictive insights to guide biomaterial design, disease diagnosis, and therapeutic strategies. This talk highlights the pivotal role of computational modeling in unraveling intricate biological processes, with a focus on two current studies. First, brain development mechanics explores the interplay between cortical folding patterns and neural connectivity during neurodevelopment. Combining neuroimaging data with computational biomechanics models, this research deciphers how differential growth and axonal wiring contribute to cortical folding variability and regularity, offering mechanistic insights into brain structure-function relationships and neurodevelopmental disorders. Second, nano-bio interface mechanics investigates how nanoparticle properties—such as surface chemistry, shape, and stiffness—govern cellular uptake and release dynamics. By integrating multiscale simulations, this work establishes design principles for optimizing nanomaterial-biological tissue interfacial properties while maintaining the structural integrity. Finally, this talk concludes with the PI’s future research vision on blending AI and data-driven computational mechanics with biomechanics applications.

Biography: Dr. Xianqiao (XQ) Wang now is a Full Professor of Mechanical Engineering at University of Georgia, the Graduator Coordinator of Mechanical Engineering program, and Co-Director UGA Center for Brain-inspired Artificial Intelligence. He obtained his Ph.D. degree in Mechanical Engineering from the George Washington University in 2011, and later he joined the University of Georgia as an Assistant Professor. He has published more than 150 peer-reviewed papers in top international journals such as Advanced Materials, Science Advances, ACS Nano, Advanced Functional Materials, Brain Structure and Functions, Cerebral Cortex, Human Brain Mapping, etc. He is a Fellow of the American Society of Mechanical Engineers (ASME), the recipient of the International Conferences on Computational Methods (ICCM) Young Investigator Award, and the recipient of the College of Engineering Excellence in Instruction. His research interests focus on data-driven brain mechanics, bio-inorganic interfaces, materials design using AI, and soft matter. His current work is funded by NSF, NIH, USDA, DoE/IES grants.

The lecture will take place in person and will also be streamed via Zoom.

To receive the Zoom link, please contact andrea.dakkouri@fau.de.