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Principal Investigator (PI) - Brian Munsky

Current Position

  • (2014-Present) Assistant Professor; Chemical and Biological Engineering; Colorado State University, Fort Collins CO
  • (2014-Present) Assistant Professor; School of Biomedical Engineering; Colorado State University, Fort Collins CO
  • (2016-Present) Keck Scholar; Colorado State University, Fort Collins CO

Previous Positions

  • (2010-2016) Research Scientist; New Mexico Consortium; Los Alamos NM
  • (2013); Scientist II, Los Alamos National Laboratory; Los Alamos, NM
  • (2010-2013); Richard P Feynman Distinguished Postdoctoral Fellow in Theory and Computing; Los Alamos National Laboratory; Los Alamos, NM
  • (2008-2010); Director's Postdoctoral Fellow; Los Alamos National Laboratory; Los Alamos, NM



  • NIGMS Maximizing investigator Research Award (MIRA, R35): "Using Cellular Fluctuations and Computational Analyses to Probe Biological Mechanisms," Sponsored by HHS-NIH-National Institutes of Health (September 15, 2017 - August 31, 2022). PI.
  • DTRA "Bet-hedging in Pathogens: Targeting Bacterial Persistence to Combat Infectious Disease," Sponsored by DOE-NNSA-Los Alamos National Laboratory. (January 17, 2017 - December 31, 2017), co-I.
  • W. M. Keck Foundation Medical Research Area Grant, "Quantifying Multiplexed Real-Time RNA to Protein Translation in Live Cells", (July 1, 2016 - June 30, 2020), co-PI.
  • NIH R25, "The q-bio Summer School", (Jan. 01 2012 - Dec. 31, 2016), co-PI.
  • NSF/I2CAM Workshop Support Award ($25,000 in support), 2011, PI.


  • Los Alamos National Laboratory Postdoctoral Distinguished Performance award, 2012
  • SIAM Conference in the Life Sciences (LS10) Poster Award, 2010
  • Leon Heller Postdoctoral Publication Prize in Theoretical Physics, 2010
  • Richard P. Feynman Distinguished Postdoctoral Fellowship, 2010
  • UCSB Department of Mechanical Engineering Best Ph.D. Dissertation for the 2007-2008 Academic Year, 2009
  • Los Alamos National Laboratory Directors Postdoctoral Fellowship, 2008
  • Best Presentation in Session, 27th American Controls Conference, 2008
  • UCSB Student Travel Grant, 2007
  • UCSB Department of Mechanical Engineering Graduate Research Fellowship, 2003
  • UCSB Chancellor's Graduate Research Fellowship, 2003
  • National Defense Science and Engineering Graduate Fellowship, 2001
  • American Helicopter Society Vertical Flight Foundation Award, 1999 and 2000
  • Penn State University Schreyer Ambassador Travel Grant, 1999
  • Mary Ilgen Memorial Scholarship, 1999
  • Schreyer Honors College Academic Excellence Award, 1996

Current Team Members


Luis Aguilera

I obtained my Ph.D. in Biomedical Engineering and Physics at the Center for Research and Advanced Studies of the Mexican National Polytechnic Institute in collaboration with the University of Heidelberg, Germany. Currently, I am a WM Keck Postdoctoral Scholar at the Colorado State University in the group of Dr. Brian Munsky. During my postgraduate studies, I have developed high-performance computing technologies that are applied in the field of molecular virology and gene expression. As a result of my work, I have generated publications in international scientific journals with recognized impact factor, and international groups have cited those publications. My current research involves the design of efficient computational algorithms to integrate gene expression data with stochastic models.  


Email: Luis.aguilera at




  • Aguilera LU, Galindo BE, Sánchez D & Santillán M (2012) What is the core oscillator in the speract- activated pathway of the Strongylocentrotus purpuratus sperm flagellum? Biophysical Journal 102: 2481– 2488.
  • Aguilera LU & Rodríguez-González J (2014) Studying HIV latency by modeling the interaction between HIV proteins and the innate immune response. Journal of Theoretical Biology 360: 67–77.
  • Aguilera LU, Zimmer C, Kummer U (2017). A New Efficient Approach to Fit Stochastic Models on the Basis of High-throughput Experimental Data Using a Model of IRF7 Gene Expression as Case Study. BMC Systems Biology. 11:26.
  • Aguilera LU, Zimmer C, Rodríguez-González J (2017). Modeling the Effect of Tat Inhibitors on HIV Latency. Submitted to Physical Biology.

 Linda Forero Quintero

I obtained my PhD in natural sciences in 2016 from the university of Kaiserslautern, Germany. During my PhD research, I worked on Neurosciences and Brain Energy Metabolism. I particularly characterized the role of monocarboxylate transporters (MCTs) during epileptiform activity using pH and Ca2+ imaging. Currently, I am WM keck postdoctoral scholar at Colorado State University, working under the supervision of Dr. Brian Munsky and Dr. Tim Stasevich. In my present research, I will be developing new technology to enable multiplexed single molecule imaging of gene expression in living cells and in real time.


Email: Linda.Forero_Quintero at




  • Francisco J. Sierra-Valdez, Linda S. Forero-Quintero, Patricio A. Zapata-Morin, Miguel Costas, Arturo Chavez-Reyes, Jesús C. Ruiz-Suárez. (2013). The influence of non-polar and polar molecules in mouse motile cell membranes and pure lipid bilayers. PloS-One. DOI: 10.1371/journal.pone.0059364.
  • Valdebenito, R., Ruminot, I., Garrido-Gerter, P., Fernández-Moncada, I., Forero-Quintero, L., Alegría, K., Becker, H.M., Deitmer, J.W., Barros, L.F. (2015). Targeting of astrocytic glucose metabolism by beta-hydroxybutyrate. Journal of Cerebral Blood Flow & Metabolism. DOI: 10.1177/0271678X15613955.
  • José, P. Torres-Rodríguez, L. S. Forero-Quintero, J. C. Chávez, J. L. de la Vega-Beltrán, F. Carta, C. T. Supuran, J. W. Deitmer, C. L. Treviño (2015). Carbonic anhydrases and their functional differences in human and mouse sperm physiology. Biochem. Biophys. Res. Commun. DOI: 10.1016/j.bbrc.2015.11.021.
  • Forero-Quintero, L.S., Becker, H.M., Deitmer, J.W., (2017). Reduction of epileptiform activity in ketogenic mice: The role of monocarboxylate transporters. Scientific reports. DOI: 1038/s41598-017-05054-0

Huy Vo

I obtained my Math Ph.D. in 2017 from the University of Alabama. I am interested in applying new methods in numerical linear algebra into solving high-dimensional problems in quantitative biology. I’m currently working on algorithms for simulating heterogeneous populations, and methods for parameter identification of stochastic gene expression models. My aim is to develop efficient codes in Fortran, C++ and MPI for the analysis of single-cell and single-molecule data sets.




Email: Huy.Vo at




  • H. D. Vo and R. B. Sidje. Adaptive solution to the chemical master equation using tensors. Journal of Chemical Physics, Volume 147, Issue 4, July 2017.
  • H. D. Vo and R. B. Sidje. Approximating the large sparse matrix exponential using incomplete orthogonalization and Krylov subspaces of variable dimensions. Numerical Linear Algebra with Applications, Volume 24, Issue 3, May 2017.

Graduate Students

Zachary Fox (Ph.D. 2019, now at Institut Pasteur, Paris, France)

I started my PhD in Biomedical Engineering at Colorado State University in 2016.  During my time here, I have worked on developing new tools to integrate modern single-cell, single-molecule biological data set with discrete stochastic models. These mathematical and computational tools allow for faster model identification and uncertainty quantification while still making use of the rich information provided by single cell data. I collaborate closely with groups that work on live-cell imaging of translation, and signal-activated gene expression in yeast. 

Email: zrfox at


  • L. Aguilera, W. Raymond, Z. R. Fox, M. P. May, E. Djokic, T. Morisaki, T. J. Stasevich, B. Munsky, Computational design and interpretation of live-cell, single-RNA translation experiments, PLoS Computational Biology, 2019, online here
  • Z. Fox, B. Munsky, The finite state projection based Fisher information matrix approach to estimate and maximize the information in single-cell experiments, PLoS Computational Biology15:1, e1006365, 2019, online here
  • H.D. Vo, Z.R. Fox, A. Baetica, B. Munsky, Bayesian estimation for stochastic gene expression using multifidelity models, J Physical Chemistry B, 123:10, 2217-2234, 2019, online here
  • B. Munsky, G. Li, Z. Fox, D. P Shepherd, G. Neuert, Distribution shapes govern the discovery of predictive models for gene regulation, Proceedings of the National Academy of Sciences USA, 115:29, 7533-7538 (2018), online here
  • Z Fox, B Munsky, Stochasticity or Noise in Biochemical Reactions, in Quantitative Biology: Theory, Computational Methods and Examples of Models, edited by B Munsky, L S Tsimring, and W S Hlavacek, MIT Press, ch. 5 (2018). arXiv version
  • Z. Fox, G. Neuert and B. Munsky, Finite state projection based bounds to compare chemical master equation models using single-cell data, Journal of Chemical Physics145:7, 074101 (2016), online here
  • B. Munsky, Z. Fox, G. Neuert, Integrating Single-Molecule Experiments and Discrete Stochastic Models to Understand Heterogeneous Gene Transcription, Methods85, 12-21, (2015), online here
  • Nonspecific transcription factor binding can reduce noise in the expression of downstream proteins
    M Soltani, P Bokes, Z Fox, A Singh, Physical biology 12 (5), 055002
  • Disorder, oscillatory dynamics and state switching: the role of c-Myc
    N Rangarajan, Z Fox, A Singh, P Kulkarni, G Rangarajan, Journal of Theoretical Biology 386, 105-114
  • Stochastic analysis of protein-mediated and microRNA-mediated feedback circuits in HIV
    Z Fox, A Singh, IFAC Proceedings Volumes 47 (3), 1146-1151

Michael May

My work focuses on branching the gap between theoretical quantitative biology and traditional microbiology wet-labs. Currently, I am working on using the variability predicted in stochastic models as a tool to help identify genes imaged though new techniques developed by a collaborator at CSU. My background is in biomedical and chemical engineering and my interests are in modeling and simulation.

Email: michael.may at



William Raymond


Mohammad Tanhaemami

I currently focus on data analysis of flow cytometry measurements to provide label-free quantification strategies to identify intrinsic properties of single cells. Based upon population statistics and machine learning, I integrate labeled and unlabeled training data and identify models for accurate label-free quantification.


Email:  mtanha at




Jaron Thompson

I received Bachelors degrees in Chemical and Biological engineering and in Biomedical engineering from Colorado State University in May 2018. As a current MS candidate in Chemical engineering, I am interested in applying machine learning approaches to model microbial community interaction networks in the context of carbon fixation. Other research interests include modeling, optimization, and stochastic simulation of biological processes.



Thompson J, Johansen R, Dunbar J, Munsky B (2019). Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition. PLOS ONE 14(7): e0215502.


Lisa Weber

I received an MS in Mechanical Engineering with a biological emphasis from the University of Denver in 2012. I am currently a PhD student in Chemical Engineering at Colorado State University. My research has included computational modeling of various aspects of RNA translation, which can be utilized in the analysis of single-cell data. Additionally, I am collaborating with an experimental group and performing computational modeling of their DNA / oligonucleotide binding dynamics experiments at various experimental conditions, including fitting and prediction, while taking into consideration multiple experimental variables simultaneously. I am also incorporating these modeling tools into a GUI to enable the experimental group to perform similar analyses on future experiments. In addition, I am a Graduate Teaching Fellow and the Instructor for the Introduction to MATLAB for Engineers course (CBE160). I was also the Graduate Teaching Fellow for the Introduction to Chemical Engineering course (CBE101) for the 2017-2018 academic year and taught the laboratory sessions.  As a Graduate Teaching Fellow, I am performing research on approaches for teaching implicit bias and diversity related topics to undergraduate engineering students. 


Email: llweber at



  • L. Weber, W. Raymond, and B. Munsky. (2018) Identification of gene regulation models from single-cell data. Physical Biology, 15 (5), 055001.
  • L. Weber, W. Raymond, and B. Munsky, “Tutorial on the Identification of Gene Regulation Models from Single-Cell Data,” in Quantitative Biology: Theory, Computational Methods, and Models, B. Munsky, W. S. Hlavacek, and L. S. Tsimring, Ed. Cambridge, MA: The MIT Press, 2018, pp. 599-616.
  • M.S. Thesis“Pulmonary particle deposition in relation to age, body weight, and species”
    • Deposition based on therapeutic volume delivered and determined by static probabilistic mathematical model.  Evaluation of deposition based on variable breathing rates. Sensitivity analysis performed to determine sensitivity of particle deposition to changes in particle size and breathing rate.
  • Worden RN, Weber LM, and Lengsfeld CS. September 2012. Optimal Parameters for Pulmonary Particle Deposition as a Function of Age.ICLASS 2012, 12th  International Conference on Liquid Atomization and Spray Systems. Heidelberg, Germany.
  • Weber LM and Lengsfeld CS. May 2011. Spray Nebulizer Deposition Efficiency as a Function of Age. ILASS Americas, 23rd Annual Conference on Liquid Atomization and Spray Systems, Ventura, CA (Best Conference Paper Finalist).
  • Weber LM and Lengsfeld CS. May 2011. Spray Nebulizer Deposition Efficiency Impact of Species. ILASS Americas, 23rd Annual Conference on Liquid Atomization and Spray Systems, Ventura, CA.

Undergraduate Students

Elliot Djokic

Charis Ellis

Research Assistants


Will Raymond

I graduated in May 2017 from Colorado State University with a Bachelors in Biomedical Engineering and a Bachelors in Chemical and Biological Engineering. I am working on a stand alone Python module that eventually will be released as an open source software. The goal of the project is to provide ease of access to generating, solving, and analyzing Finite State Projection solutions to experimentalists for a myriad of time series data.





Email: williamscottraymond at



  • Chase Hunter, Undergraduate, Chemical and Biological Engineering. Now a Defect Analysis Engineer at Micron Technology, Inc.
  • Charlotte Mitchell, Undergraduate, Chemical and Biological Engineering and Biomedical Engineering (Dual Degree). Now a Quality Assurance Engineer at Raytheon.
  • Lucas Suazo, Undergraduate, Chemical and Biological Engineering and Biomedical Engineering (Dual Degree). Now at Stanford Medical School.
  • Douglas Shepherd , Postdoc, Now Assistant Professor of Pharmacology at University of Colorado Anschutz Medical Campus.