Scholar
Michael Stanley
Google Scholar ID: Q0BUuc0AAAAJ
Analytical Mechanics Associates
Citations & Impact
Citations
39
H-index
3
i10-index
2
Publications
13
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Published several papers in the fields of statistical inverse problems and uncertainty quantification, including 'Optimization-based frequentist confidence intervals for functionals in constrained inverse problems: Resolving the Burrus conjecture' and 'Estimating Posterior Uncertainty via a Data Assimilation Specialized Monte Carlo Procedure'.
Research Experience
- Currently a Research Scientist at NASA Langley Research Center through Analytical Mechanics Associates, working on uncertainty quantification research. He was also a MLIA Summer Intern at Jet Propulsion Laboratory, researching gradient-free optimizations and developing a codebase for decision theoretic uncertainty quantification. Previously, he worked as a Senior Data Scientist at tellic, focusing on pharmaceutical text data to support NLP technology.
Education
- PhD in Statistics & Data Science from Carnegie Mellon University in 2024, under Mikael Kuusela; M.S. in Statistics from Carnegie Mellon University in 2016; B.S. in Mathematics from Baylor University in 2015.
Background
- A Research Scientist primarily interested in application-driven statistical methodological development and implementation, particularly at the intersection of optimization, Machine Learning, and large-scale computing. At NASA, he works on engineering and materials problems while also building the uncertainty quantification community across NASA.
Miscellany
- Served as the Lead Instructor for a Data Science Summer Camp at the Department of Statistics & Data Science, Carnegie Mellon University, from June to July 2022, organizing a week-long camp with lectures and interactive coding activities. Also, he has been a Teaching Assistant for multiple courses and an Advisor for the Data Science Initiative at the same department.
Co-authors