2041 N. College Rd.
Columbus, OH 43210
Michael is a member of CAMM. He is currently working on several small projects while focusing primarily on core classes before beginning a research project. His current and past efforts include:
- Developing a program in Matlab in order to train and evaluate Bayesian multilayer perceptron neural networks for regression problems linking microstructural feature measurements to material properties.
- Using Bayesian neural nets to generate virtual experiments exposing the predicted trends in yield strength with the variation of individual microstructural features, as well as attempting to use those predictions to examine variance in current stereological techniques.
- Investigations of ‘checkmark’ type α precipitates in titanium. He generated the microstructure using heat treatments in an ETMT (Electro Thermal Mechanical Tester) and carried out the characterization using SEM and 3D reconstructions based on FIB serial sections.
- Rebuilding and operating a UHV Magnetron Sputtering machine.
- Using characterization techniques to determine doping site occupancies in Nb3Sn.
- "Characterization of "check-mark" Alpha Precipitate in Titanium Alloys Using 2D and 3D Characterization Techniques.." 2011, Presented at Material Science and Technology Conference (MS&T),
- "Virtual Experiments and Neural Networks: Evaluating the effect of microstructural features in Ti-based Alloys using Matlab." 2012, Presented at Material Science and Technology Conference (MS&T),