Educational Background

Florida State University
Ph.D. in Statistics

Florida State University
Master of Science in Statistics

Idaho State University
Bachelor of Science in Statistics

Current Courses

Linear Algebra

Selected Publications

Medford, A. J., Kunz, M. R., Ewing, S. M., Borders, T., and Fushimi, R. (2018). Extracting knowledge
from data through catalysis informatics. ACS Catalysis, 8(8):7403–7429.

Kunz, M. R., Kalivas, J. H., and Andries, E. (2010a). Model updating for spectral calibration
maintenance and transfer using 1-norm variants of tikhonov regularization. Analytical chemistry,
82(9):3642–3649.

Chen, B.-R., Kunz, M. R., Tanim, T. R., and Dufek, E. J. (2021). A machine learning framework for
early detection of lithium plating combining multiple physics-based electrochemical signatures. Cell
Reports Physical Science, 2(3):100352.

Kunz, M. R., Yonge, A., Fang, Z., Batchu, R., Medford, A. J., Constales, D., Yablonsky, G., and
Fushimi, R. (2021). Data driven reaction mechanism estimation via transient kinetics and machine
learning. Chemical Engineering Journal, page 129610.

Kunz, M. R. and She, Y. (2013). Multivariate calibration maintenance and transfer through robust fused
lasso. Journal of Chemometrics, 27(9):233–242.

Research

Application of interpretable AI, i.e., statistical learning, to a variety of different topics such as Complex Systems, High-Dimensional Penalized Regression, Time Series Analysis and Stochastic Processes, Robust Estimation, Anomaly Detection, Data-driven Chemical Kinetics, Chemometrics.