Education

PhD. Bioengineering, Colorado State University

B.S. Chemical and Biolgical Enginering, Colorado State University

B.S. Biomedical Engineering, Colorado State University

Experience

Architected and developed an image acquisition, and smart microscopy software in Python using machine learning, test driven development, program architectures, & design patterns which was 4X faster than a human

Developed distributed computing for machine learning & computer vision in Python to analyze the information content of fluorescent microscopy experiments which led to a research talk at APS 2023 and a $75,000 grant

Worked in interdisciplinary team to create custom electromechanical & optical system by machining components, developing electronic breadboards, & developing driver software to fit existing device interfaces in C++11

Optimized stochastic systems biology models for gene regulation using MATLAB over a Linux HPC which led to a publication in ACS Synthetic Biology, a talk at American Physical Society, and a biorxiv preprint

Outreach

Educated middle school students in thermodynamics for the Science Olympiad once per week for one year

Developed the most popular lectures at quantitative biology summer school for two years in a row

Spoke at the CSU 1st Generation Bioengineer dinner event to guide and motivate other 1st generation engineers (2016 to 2019).

Publications

Biochemical noise enables a single optogenetic input to control identical cells to track asymemetric and asynchronous reference signals. May, & Munsky. biorxiv preprint

Exploiting Noise, Non-Linearity and Feedback for Differential control of multiple synthetic cells with a single optogenetic input. May, & Munsky. ACS Synth Biol.

Computational Design and Interpretation of Single-RNA Translation Experiments. Aguiliera, et al. Plos Computational Biology.

Using Mechanistic Models and Machine Learning to Design Single-Color Multiplexed Nascent Chain Tracking Experiments. Raymond, et al. Frontiers in Cell Dev Biol.

Presentations

Using Stochastic Models to Extend the Color Palette of Single-Molecule Microscopy (Contributed Talk & Poster). Qbio Conference 2017

Three Pillars of Stochastic Control: Autoregulation, Noise, and Feedback (Contributed Talk). APS March 2021

Experimental Quantification of Model Identifiability and Information Loss Due to Distortions in Fluorescence Microscopy and Image Processing (Contributed Talk). APS March 2023