Rate My Professor Anthony Kearsley

Johns Hopkins University

Mathematics Chemistry Computer Science Engineering Health Science Applied Mathematics Computational Mathematics Statistics Machine Learning Data Mining

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5.03/25/2026

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About Anthony

Anthony Kearsley is a Lecturer in the Department of Applied Mathematics and Statistics at Johns Hopkins University. He earned his Ph.D. in Computational and Applied Mathematics from Rice University, with a dissertation entitled "The Use of Optimization Techniques in the Solution of Partial Differential Equations from Science and Engineering." Currently, he serves as a Mathematician in the Mathematical Analysis and Modeling Group of the Applied and Computational Mathematics Division at the National Institute of Standards and Technology (NIST), where he conducts research in applied mathematics.

Kearsley's research specializations include large-scale nonlinear optimization, numerical methods for shape optimization, uncertainty quantification in diagnostic testing, mass spectral analysis, cryoprotectant optimization, antibody kinetics modeling, flow cytometry, and machine learning applications in physiologically-based pharmacokinetic modeling and bioelectronic sensors. His work has appeared in prestigious journals such as Analytical Chemistry, SIAM Journal on Optimization, International Journal for Numerical Methods in Fluids, and mAbs. Notable publications include "Combining fragment-ion and neutral-loss matching during mass spectral library searching: a new general purpose algorithm applicable to illicit drug identification" (2017, Analytical Chemistry, 120 citations), "The solution of the metric STRESS and SSTRESS problems in multidimensional scaling using Newton's method" (1995, 114 citations), "Enabling adoption of 2D-NMR for the higher order structure assessment of monoclonal antibody therapeutics" (2019, 99 citations), "Numerical simulation and optimal shape for viscous flow by a fictitious domain method" (1995, 99 citations), "A practical algorithm for general large scale nonlinear optimization problems" (1999, SIAM Journal on Optimization, 95 citations), and "Mathematical optimization of procedures for cryoprotectant equilibration using a toxicity cost function" (2012, 93 citations). With over 1,600 citations across more than 160 publications documented on Google Scholar and ResearchGate, Kearsley's contributions have significantly influenced intersections of mathematics, computational sciences, and biomedical applications. He has received the Washington Academy of Science Award for Excellence in Research, as well as NIST awards including recognition for pioneering real-time, cell-scale anomaly detection algorithms in semiconductor fabrication. At Johns Hopkins University, Kearsley teaches courses such as EN.553.602 Research and Design in Applied Mathematics: Data Mining.