Robert Luke
Member Of Research Staff at Deepgram
Melbourne, Victoria, United States
Summary
🤩
Rockstar🎓
Top SchoolRobert Luke is a research-focused engineer with 11 years of experience bridging neuroscience, signal processing, and applied machine learning, currently serving as Member of Research Staff at Deepgram in Melbourne. He holds a PhD in Neuroscience from KU Leuven and dual engineering and physics degrees from the University of Melbourne, and has moved between academia and industry roles—from postdoc research to senior DSP work at Cirrus Logic and founding a startup—demonstrating both deep technical rigor and product-facing impact. Robert contributes to prominent open-source projects like MNE-Python, where he implemented fNIRS and SNIRF processing pipelines and practical features such as Beer-Lambert law support, highlighting a niche expertise in neuroimaging data engineering. Colleagues would describe him as someone who translates complex electrophysiology problems into robust, reusable software and production-ready signal processing solutions.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (PhD), Neuroscience, Doctor of Philosophy (PhD), Neuroscience at KU LeuvenInstitute of Communication Acoustics, Institute of Communication Acoustics at Ruhr University BochumThe University of Melbourne
English
Stackoverflow
128reputation
24kreached
1answer
1question
Github Skills (8)
python10
data-analysis10
signal-processing9
numpy9
h5py8
julia6
multidimensional-arrays6
matplotlib6
Programming languages (14)
Github contributions (5)
mne-tools/mne-python
Sep 2019 - Jan 2023
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:203 reviews, 90 commits, 104 PRs in 3 years 3 months
Contributions summary:Robert primarily worked on implementing and improving fNIRS data processing pipelines within the MNE-Python library. They developed features for reading and processing SNIRF data, including support for different file structures and the handling of optical density data. Further contributions focused on integrating new features for fNIRS data, such as support for data from Artinis and the implementation of the Beer-Lambert law.
visualizationneuroimagingneurosciencepythonstatistics
rob-luke/fnirs-apps-quality-reports
Jun 2021 - Mar 2022
fNIRS Apps: Quality Reports
Contributions:25 releases, 79 commits, 40 PRs in 8 months
reportsqualityfnirs
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