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Professor Sundararaghavan's interests are in the areas of computational mechanics, multi-scale materials modeling and optimization with emphasis on prediction and design of property distributions in polycrystalline materials and composites. Multi-scale models resolve interactions of material structure and mechanisms occurring over various length and time scales. His interest is on developing multi-scale computational models to address material design and optimization problems; examples include prediction of optimal processes to obtain desired strength, stiffness and fracture toughness in polycrystalline microstructures using finite element homogenization or molecular dynamics approaches and identification of optimal phase structures with desired magnetic/thermal properties using ab-initio simulations and statistical mechanics approaches. A variety of techniques including linear programming, gradient optimization and modern statistical learning methods are used to develop design solutions. He has made seminal contributions towards the development of mathematical model reduction techniques for accelerated materials-by-design including methods for graphical visualization of high dimensional material property-structure spaces and adaptive reduced order optimization.
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