PhD candidate in the Industrial Engineering and Management Sciences (IEMS) department. Developed adaptive methods for computer experiments when data is limited, implement in R for demonstration. Integrated ideas from design of experiments, regression modeling, sequential design, and active learning. Devised algorithm for performing adaptive computer experiments that balances multiple objectives. Implemented algorithms in R to demonstrate efficacy.

Improved machine learning pipeline for Catalina Sky Survey (CSS) near-Earth asteroid detection system. Trained CNNs in TensorFlow on telescope images and metadata, improved asteroid detection by 10%. Planned infrastructure for manned mission to Mars for intern project to be presented to company leadership.

Developed models for predicting viscosity curves of glass compositions to accelerate glass discovery process. Combined machine learning with physics-based models improve model ability and extrapolation. Used TensorFlow and MATLAB to create models based to leverage Corning's historical data.

Developed algorithm for conducting adaptive computer simulations for the SEED Center for Data Farming. Incorporated ideas from modeling, experimental design, and sequential algorithms to allow simulations to focus on results interesting to the user. Fused experimental design and sequential algorithms to focus simulation effort on results desired by user.

I tutored students who came for help for their math and physics courses.

I tutored students who came for help for their first-year physics courses.

Employer: Vanderbilt University Hospital, Surgical PathologyPosition: Lab AssistantStart Date: 2/7/2011End Date: 5/6/2011Type of Work: I worked in the surgical pathology gross room. I mainly did stocking and cleaning, along with other various tasks.