Summary
Rebecca Krall is a data scientist and Assistant Director with a decade of experience applying machine learning and signal-processing methods to neuroscience, behavioral, video, and business text data. She builds end-to-end pipelines—from experiment design and large-scale ETL to model training and user-facing apps—that have automated manual workflows (e.g., mouse behavior scoring) and cut analysis times by orders of magnitude. Her technical toolkit spans Python (TensorFlow, Keras, scikit-learn, OpenCV, Pandas), MATLAB, and deployment tools like Streamlit and PyInstaller, and she has a track record of shipping production-ready deep learning and document-processing systems that materially speed stakeholder workflows. In academic settings she developed GLM and GLM-HMM analyses on multi-terabyte neural and video datasets and led collaborative teams producing conference and journal outputs. Pragmatic and communicative, she pairs a neuroscience foundation with a product-minded, get-things-done approach to turn noisy experimental data into interpretable, actionable insights.
10 years of coding experience
10 years of employment as a software developer
Bachelor of Science - BS Neuroscience, Bachelor of Science - BS Neuroscience at University of Pittsburgh