Papers
Below is a selection of published scientific work exploring machine learning, physics, and computational methods for understanding complex systems.
Machine Learning
Comparing Machine Learning Architectures on Biophysics Data
Biophysical Journal, 2025
A comparison of machine learning architectures for analyzing imaging and biophysical datasets.
Energy Landscape Inference
Learning Potential Energy Landscapes in FRET
Biophysical Journal, 2022
My favorite paper! We reconstruct full molecular binding energy landscapes despite having no direct measurements of the underlying potential surface.
Inferring Effective Forces for Langevin Dynamics
Journal of Chemical Physics, 2020
By tracking particle motion, we infer the invisible force fields governing stochastic dynamics.
Inferring Potential Energy Landscapes with Measurement Noise
iScience, 2022
An extension of the original method that incorporates measurement noise and improves scalability for larger systems.
Microscopy & Imaging
Diffraction-Limited Molecular Cluster Quantification with Bayesian Nonparametrics
Nature Computational Science, 2022
Methods for counting molecular clusters even when they cannot be visually resolved due to diffraction limits.
Structured Illumination Microscopy
Communications Engineering, 2024
Computational methods for structured illumination microscopy, enabling imaging below the diffraction limit.
Mapping Diffusion Coefficient Maps on Cell Membranes
Biophysical Reports, 2024
Methods for reconstructing spatial diffusion and friction maps on biological membranes.
Stochastic Dynamics & Molecular Motion
Analyzing Bacteria Swimming Behavior
Biophysical Journal, 2023
Analysis of bacterial swimming dynamics, showing how bacteria regulate motion to conserve energy in low-resource environments.
Molecular Centrifuge Analysis
Journal of the American Chemical Society, 2023
Analysis methods for molecular centrifuge experiments used to probe molecular binding energetics.
Quantifying Binding Kinetics
Journal of Physical Chemistry B, 2025
Methods for learning molecular binding and unbinding rates from indirect stochastic observations.
Dissertation
My PhD Dissertation
Arizona State University, PhD Dissertation
Research on statistical inference methods for stochastic biophysical systems, molecular dynamics, and single-molecule experiments.
Google Scholar
Additional publications and citation information can be found on my Google Scholar profile.