* Performed original research in computational microscopy and image reconstruction with photophysical models, using maximum likelihood, Bayesian inference, deep learning (e.g. Keras, TensorFlow)

* Developed signal processing methods to improve signal-to-noise ratio (SNR) in fluorescence microscopy

* Trained and supported ~50 biologists w/ use of Micro-Manager, an open source Java/C++ microscope control software package

* Developed hardware interaction code, both for Micro-Manager (C++) and custom in-house work (Python)

* Expertise in scientific Python (e.g. numpy, scipy, matplotlib, scikit-image, pandas, scikit-learn)

* Developed new approach for 3d structured illumination microscopy (SIM) reconstruction using maximum likelihood estimation

* Implemented multiprocessing SIM algorithm in Python, including routines for point spread function fitting and illumination inference

* Designed and built tunnel junction devices for proof-of-principle experiment demonstrating novel nonlinear capacitive measurement for detecting Majorana fermions in nanowires

* Built custom low-capacitance cryogenic probe for lock-in measurement of test devices