Dr. Tao Jin received both his Bachelor of Engineering and Master of Engineering degrees from Tongji University in Shanghai, China. After working for two years as a structural engineer in the energy industry, he attended Rice University in Houston, Texas, USA and obtained his Ph.D. degree in 2016. Dr. Jin then joined Los Alamos National Laboratory in Los Alamos, New Mexico, USA, where he worked for three years as a Postdoctoral Research Associate in the Fluid Dynamics & Solid Mechanics Group, Theoretical Division. In 2019, he moved to Livermore, California, USA and joined Lawrence Livermore National Laboratory’s Atmospheric, Earth & Energy Division, where he worked as a Postdoctoral Research Associate in the Computational Geoscience Group. Dr. Jin joined the Department of Mechanical Engineering at uOttawa in 2021 as an Assistant Professor. In his spare time, he plays soccer and guitar.
Dr. Jin’s research focuses on developing accurate, robust, and scalable numerical techniques and computational strategies to model, predict, and optimize complex material and engineering systems. Using advanced simulation techniques, his vision is to deepen scientific understanding of complex material systems, such as native tissues and soft matter, and to drive technological transformations in medical devices, additive manufacturing, flexible electronics, and renewable energy. Dr. Jin’s past research in different topics laid the framework for his current explorations. His PhD research at Rice University focused on multiscale simulation techniques to investigate material properties of various biological tissues and bioinspired materials, such as heart valve tissues, arterial walls, and functional hydrogels. At Los Alamos National Laboratory, he developed novel computational strategies based on crystal plasticity and damage mechanics to treat dynamic strain localization and fracture propagation in metallic materials and alloys. Currently, he is collaborating with researchers from Lawrence Livermore National Laboratory to design robust numerical techniques for the simulation of field-scale fracture propagation in porous media driven by injected viscous fluid.
Dr. Jin’s current research interest includes: (1) integration of physics-based numerical strategies with modern data mining and machine learning techniques for the modeling, engineering design, and optimization of emerging complex material systems; (2) multiscale computational homogenization and uncertainty quantification to bridge material structure-function relationships; (3) development of numerical techniques applicable to field-scale solid-fluid-thermal coupled systems for the prediction and improvement of geothermal energy harvesting performance.