This workshop is sponsored by the TMS Materials Processing & Manufacturing Division and TMS ICME Committee, with support offered by AFOSR-MURI, NIST, and Georgia Tech’s IMAT.

Please note: TMS workshops will be held in the Crowne Plaza Hotel—TMS Headquarters Hotel for MS&T15. MS&T15 registration, exhibit, and technical sessions will be held at the Greater Columbus Convention Center.

Scope
Microstructure informatics is an emerging suite of advanced statistical tools and data science methods tailored specifically to the quantification of the hierarchical internal structure (also called microstructure) and the extraction of process-structure-property (PSP) relationships in materials science. The purpose of the materials informatics workshop is to provide practical knowledge in using these techniques to improve the efficiency and efficacy of multiscale simulations and experimental characterization involving materials microstructure (see below for detailed workshop outline). The workshop will focus on introducing participants to a set of open source computational tools in Python that address foundational components of the emerging materials informatics.

The techniques covered in the workshop are useful to any materials scientist and are especially relevant to many of the challenges associated with the practical realization of the goals of the Materials Genome Initiative. The workshop will allow participants to significantly augment their existing workflows involving microscale and continuum simulations or experimental characterization to enable more efficient processing of large ensembles of datasets.

Who Should Attend?
This course is designed for graduate students, post-docs, and researchers interested in learning how their research in materials science and engineering can benefit from the emerging tools and concepts in materials data analytics and cyberinfrastructure. Furthermore, those researchers interested in scientific computing with Python in the realm of materials science will also benefit from the workshop.

Workshop Outline

Surya R. Kalidindi earned a Ph.D. in mechanical engineering from the Massachusetts Institute of Technology. He then joined the Department of Materials Science and Engineering at Drexel University as an assistant professor, where he served as the department head from 2000–2008. In 2013, Kalidindi accepted a new position as a professor of mechanical engineering in the George W. Woodruff School at Georgia Institute of Technology, with joint appointments in the School of Computational Science and Engineering and in the School of Materials Science and Engineering. Kalidindi’s research efforts over the past two decades have made seminal contributions to the fields of crystal plasticity, microstructure design, spherical nanoindentation, and materials informatics. His work has already produced about 200 journal articles, four book chapters, and a new book on Microstructure Sensitive Design. His work is well-cited by peer researchers as reflected by an h-index of 50 and current citation rate of about 1,000 citations/year (according to Google Scholar). He has recently been awarded the Alexander von Humboldt award in recognition of his lifetime achievements in research. He has been elected a Fellow of several professional societies: TMS, ASM International, ASME, and Alpha Sigma Mu.

David Brough is a Ph.D. student in the School of Computational Science and Engineering at Georgia Institute of Technology. He earned a master’s degree in experimental condensed matter physics at Brigham Young University where he fabricated and characterized thin-films used in nanostructured high capacity battery electrodes and in x-ray windows. As an undergraduate, Brough studied theoretical physics and researched the evolution of chaotic systems using neural networks at Westminster College. He is also a trainee in the National Science Foundation Integrative Graduate Education and Research Traineeship (NSF IGERT) FLAMEL program, and one of the lead developers on the PyMKS materials informatics toolkit. Brough’s current research interest is creating tools and protocols that efficiently leverage large datasets to learn structure-processing and structure-property relationships.

Yuksel Yabansu is a Ph.D. candidate in George W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology. He earned his B.S. in mechanical engineering and his M.S in automotive engineering at Istanbul Technical University. After his master’s program, he joined Surya Kalidindi’s research group MinED as a Ph.D. student with government scholarship from Turkey. Yabansu focused largely on novel framework Materials Knowledge System (MKS) early in his Ph.D. program and extended the framework for the elastic deformation of polycrystalline aggregates. His current research interest mainly lies in homogenization and localization in hierarchical multiscale modeling, machine learning techniques in materials data classification, and building processing-structure-property linkages.

Ahmet Cecen is currently pursuing a Ph.D. in computational science and engineering at the Georgia Institute of Technology. He earned a bachelor’s degree in mechanical engineering at Drexel University. Cecen has been doing research in the fields of computational materials science and materials informatics for the past six years, throughout his undergraduate and graduate studies. His current research focus is on leveraging statistical analysis and machine learning tools to solve big data analytics problems in materials science.

Registration for MS&T15 and related workshops is available through the MS&T15 website.

For more information about this meeting, please complete the meeting inquiry form or contact:

TMS Meeting Services
184 Thorn Hill Road
Warrendale , PA 15086-7514 USA
Telephone (724) 776-9000, ext. 241
(800) 759-4TMS
Fax: (724) 776-3770
E-mail: mtgserv@tms.org