Teaching
2020
Fall: MSE 2090 -- Introduction to Materials Science
- To introduce the basic principles underlying the formation, behavior, and properties of materials. This course will provide the scientific foundations for an understanding of the relationships among material properties, structure and performance for the classes of engineering solids (metals, ceramics, polymers, semiconductors and composites). Concepts will be developed and applied which allow for correlation between performance and aspects of structure, from atomic through the macroscopic level. Ideas relating to atomic and larger size defects and their influence on material behavior are included.
Spring: MSE 4592/6592 -- Introduction to Materials Informatics (Special Topics)
Materials science, like health, social and biological sciences, is at the cusp of a data revolution. Harnessing materials data by developing data-driven tools that integrate experimental data with materials models at various length and time scales will lay the foundation for a paradigm shift in the way new materials are designed, discovered and deployed in the future. The goal of this course is to inform and educate future scientists and engineers with the skill set of data analytics applied to materials science problems.
More formally, the course will cover the following topics. Uncover trends and patterns from diverse materials data using exploratory data analysis, visualization and unsupervised learning; Build structure-property relationships using supervised learning (regression and classification learning); Design of experiments and optimal design; Data-driven vs Science-driven materials informatics (Bayesian inference); No-free-lunch theorem
2019
Fall: MAE 3420 -- Computational Methods in Mechanical and Aerospace Engineering
- Introduces numerical modeling concepts used in engineering simulation tools. Topics covered inclide discretization methods of partial differential equations, numerican solutions of linear matrix equations, and relaxation techniques.
Spring: MSE 6592 -- Introduction to Materials Informatics (Special Topics)
Materials science, like health, social and biological sciences, is at the cusp of a data revolution. Harnessing materials data by developing data-driven tools that integrate experimental data with materials models at various length and time scales will lay the foundation for a paradigm shift in the way new materials are designed, discovered and deployed in the future. The goal of this course is to inform and educate future scientists and engineers with the skill set of data analytics applied to materials science problems.
More formally, the course will cover the following topics. Uncover trends and patterns from diverse materials data using exploratory data analysis, visualization and unsupervised learning; Build structure-property relationships using supervised learning (regression and classification learning); Extract meaningful materials descriptors; Design of experiments and optimal design; Data-driven vs Science-driven materials informatics (Bayesian inference); Importance of Uncertainties in Materials Exploration.
2018
Fall: MSE 2090 -- Introduction to Materials Science
- To introduce the basic principles underlying the formation, behavior, and properties of materials. This course will provide the scientific foundations for an understanding of the relationships among material properties, structure and performance for the classes of engineering solids (metals, ceramics, polymers, semiconductors and composites). Concepts will be developed and applied which allow for correlation between performance and aspects of structure, from atomic through the macroscopic level. Ideas relating to atomic and larger size defects and their influence on material behavior are included.