Materials Science and Engineering Program
June 7th
- Session Title
- 9:00-9:30 - James Warren (NIST) – “US Materials Genome Project”
- 9:30-10:00 - Surya Kalidindi (Georgia Tech) – “Data Analytics for Mining Process-Structure-Property Linkages for Hierarchical Materials”
- 10:00-10:30 - Ichiro Takeuchi (Maryland) – “Combinatorial Experimentation and Machine Learning for Materials Discovery”
- break
- 11:00-11:30 - Patrick Riley (Google) – “High-throughput screening of metal oxides”
- 11:30-12:00 - Jay Whitacre (CMU) – “An autonomous test stand driven by ML-informed decision making for co-optimized electrochemically functional materials systems: conceptual framework and progress to date”
- 12:00-12:30 - Newell Washburn (CMU) – “Machine Learning from Small Data: Modeling Response Surfaces in 3D Printing”
- 12:30-1:30 - lunch/posters
- 1:30-2:30 - plenary
- Session Title
- 2:30-3:00 - Dane Morgan (Wisconsin) – “Machine Learning Applications in Materials Data and Imaging”
- 3:00-3:30 - Jennifer Carter (CWRU) – “Mapping Multivariate Influence of Alloying Elements on Creep Behavior for New Martensitic Steels”
- 3:30-4:00 - Prasanna Balachandran (Virginia) – “Guiding the search for novel functional materials using machine learning”
- break
- 4:30-5:00 - Zi-Kui Liu (Penn State) – “Machine Learning in CALPHAD Modeling for Materials Design and Manufacturing”
- 5:00-5:30 - Tim Mueller (Johns Hopkins) – “The effective use of data in materials research”
- 5:30-6:00 - Laura Bartolo (Northwestern) – “CHiMaD Data Efforts as part of the Materials Information Infrastructure”
June 8th
- Session Title
- 8:30-9:00 - Elizabeth Holm (CMU) – “TBA”
- 9:00-9:30 - Ankit Agrawal (Northwestern) – “Materials Informatics and Big Data: Realization of 4th Paradigm of Science in Materials Science”
- 9:30-10:00 - Gilad Kusne (NIST) – “Autonomous Materials Research Systems: Phase Mapping”
- 10:00-10:30 - Olexandr Isayev (UNC) – “Cheminformatics-Inspired Materials Discovery Platform”
- break
- 11:00-11:30 - Turab Lookman (LANL) – “Accelerated search for materials with targeted properties”
- 11:30-12:00 - Anjana Talaptra (TAMU) – “Towards an Autonomous Efficient Materials Discovery Framework: An Example of Optimal Experiment Design Under Model Uncertainty”
- 12:00-12:30 - Brian DeCost (NIST) – “Active clustering for accelerated phase diagram acquisition for metal-insulator transition materials”
- 12:30-1:30 - lunch/posters
- 1:30-2:30 - plenary
- Session Title
- 2:30-3:00 - Chiwoo Park (FSU) – “Visual Analytics for Dynamic Material Imaging”
- 3:00-3:30 - Saransh Singh (CMU) – “Machine Learning of Electron Diffraction Patterns”
- 3:30-4:00 - Valentin Stanev (Maryland) – “Unsupervised Phase Mapping of X-ray Diffraction Data by Nonnegative Matrix Factorization Integrated with Custom Clustering”
- 4:00-4:30 - Jason Hattrick-Simpers (NIST) – “Iterative Machine Learning – High Throughput Experimental Platform for the Discovery of Novel Amorphous Alloys”
- 4:30-5:00
- 5:00-5:30
- 5:30-6:00
Posters
Christopher Kantzos (CMU) – “Use of Advanced Regression and Computer Vision Techniques for Evaluation of Process Parameter Modifications for Metal Additive Manufacturing”
Aditya Menon (CMU) – “Understanding particle and solution variables for optimization of dispersant composition in pozzolan modified ordinary portland cement via gaussian process regression”
Jennifer Bone (CMU) – “Developing High-Fidelity 3D Printed Biomaterial Constructs Using Hierarchical Machine Learning and Bayesian Statistical Analysis”
Brian DeCost (NIST) – “Dynamic experimental design for spatially-resolved electrochemical measurements”
Sepideh Hashemi (GT) – “Process-structure linkage for static recrystallization of cubic materials”
Andrew Castillo (GT) – “Bayesian Framework for the Estimation of the Single Crystal Parameters from Spherical Indentation Stress-Strain Measurements”
Deepak Kamal (GT) – “Polymer Genome: A Data-powered Polymer Informatics Platform for Property Predictions”
Matthew Barry (GT) – “Machine Learning for the Prediction of Atomic Displacement Energies”
Apaar Shanker (GT) – “Materials Knowledge Systems in Python (PyMKS) – An Open Source Data Science Framework for Accelerated Development of Hierarchical Materials”
David Montes de Oca Zapiain (GT) – “Prediction of the plastic response of polycrystalline materials subjected to a periodic boundary condition using Material Knowledge Systems.”
James Peerless (NC State) - "Uncertainty Quantification of Atomistic Partial Charges in Liquid Phase Molecular Dynamics"
Patxi Fernandez-Zelaia (GT) - TBD