2100 Black Engr Ames, IA 50011-2161 Phone: 515-294-7442
Indian Institute of Technology, Madras, B. Tech., Mechanical Engineering, 2003
Cornell University, MS, Mechanical and Aerospace Engineering, 2006
Cornell University, PhD, Mechanical and Aerospace Engineering, 2008
Computational physics, computational mechanics (fluid mechanics and heat transfer), stochastic analysis, uncertainty quantification and propagation, multiscale modeling, control and optimization of complex systems, materials-by-design, and parallel computing and inverse problems.
B. Ganapathysubramanian, N. Zabaras, Modeling multiscale diffusion processes in random heterogeneous media, Computer Methods in Applied Mechanics and Engineering, 197 (2008) 3560-3573.
N. Zabaras, B. Ganapathysubramanian, A scalable framework for the solution of stochastic inverse problems using a sparse grid collocation approach, Journal of Computational Physics, 227 (2008) 4697-4735.
B. Ganapathysubramanian, N. Zabaras, A non-linear dimension reduction methodology for generating data-driven stochastic input models, Journal of Computational Physics, 227 (2008) 6612-6637.
B. Ganapathysubramanian, N. Zabaras, A seamless approach towards stochastic modeling: Sparse grid collocation and data driven input models, Finite Elements in Analysis and Design, invited paper for the 19th Melosh Competition, 44 (2008) 298-320.
B. Ganapathysubramanian, N. Zabaras, Modeling diffusion in random heterogeneous media: Data-driven models, stochastic collocation and the variational multi-scale method, Journal of Computational Physics, 226 (2007) 326-353.
B. Ganapathysubramanian, N. Zabaras, Sparse grid collocation methods for stochastic natural convection problems, Journal of Computational Physics, 225 (2007) 652-685.
Creating multi-layer, squishy or solid, nanoparticles is difficult and often requires sophisticated, expensive equipment. But that didn’t stop materials science assistant professor Martin Thuo, who, with his team, run a lab where frugal science is a central theme.