• BBE (2014) Bioengineering, University of Delaware
• Ph.D. (2019) Bioengineering, Colorado State University

• Professional Training:
  • 2019-2020 Postdoctoral Researcher in Applied Mathematics and Cybergenetics at Institut Pasteur in Paris, France.

Research Interests:

• Learning models and parameters from modern single-cell microscopy data.
• Quantitative analysis of single-cell microscopy data.
• Mathematical analysis of random walks.

Selected Recent Publications:

1. Jashnsaz, Fox, Hughes, Li, Munsky, Neuert. Diverse cell stimulation kinetics identify predictive signal transduction models, iScience. 23, 10 (2020).
2. Fox, Neuert, Munsky. Optimal Design of Single-Cell Experiments within Temporally Fluctuating Environments., Complexity. 2020, Article ID 8536365 (2020).
3. Aguilera, Raymond, Fox, May, Djokic, Morisaki, Stasevich, Munsky. Computational design and interpretation of single-RNA translation experiments., PloS Computational Biology. 15(10), (2019).
4. Fox and Munsky. The finite state projection based Fisher information matrix approach to estimate and maximize the information in single-cell experiments., PloS Computational Biology. 15(1), (2019).
5. Vo, Fox, Baetica, Munsky. Bayesian estimation for stochastic gene expression using multifidelity models., Journal of Physical Chemistry B. 123(10), 2217-2234 (2019).
6. Munsky, Li, Fox, Shepherd, Neuert. Distribution shapes govern the discovery of predictive models for gene regulation., Proceedings of the National Academy of Sciences. 123(10), 2217-2234(2018).