Instrument software (C#) for R&D projects, leading development for next generation and internal instrument prototypes. Collaboration and problem solving with a diverse team of hardware, microfluidic, FPGA, and ML engineers. Designed software analysis tools for tracking the performance of single cell imaging at 1,000+ FPS.

Software development (Python, C) and algorithm optimization of the GenapSys bioinformatics pipeline. Played a significant role designing and optimizing the customer-facing version of our analysis pipeline in order to support our product launch in Q4 2019.

• Refined code via Cython, architecture changes, Unix piping (to/from samtools, bwa, bbmap, etc.), and general algorithm improvements (e.g. aho-corasick for DNA subsequence searches), delivering numerous 10x+ speedups and 3x+ reductions in RAM overhead.

• Developed pipeline for converting machine learning models trained in Tensorflow to TensorRT, boosting inference speed by 2x+.

• Created and helped manage and develop multiple GitHub repositories that interface with the primary bioinformatics pipeline.

Leading development of machine learning algorithms for radar tracking applications. Deploying convolutional neural networks on ARM microprocessors, trained in Tensorflow using data from simulations that I created in Python.