Clement Lee is a Senior Automation Engineer with 8 years of experience translating research-grade signal processing and machine learning methods into production software for life sciences and neurotech. He has a strong track record applying time-frequency analysis, clustering, kernel density estimation, and Poisson correction to real-world problems—cutting assay processing time by 70% through Golang refactors and container-first deployments. Comfortable across MATLAB, Python, C++, and Go, he’s contributed core back-end work to EEGLAB, the widely used MATLAB toolbox for EEG research, and helped build low-latency experimental tooling like Lab Streaming Layer. He excels at navigating cross-functional roadmaps and delivering AWS-backed, production-ready packages while balancing R&D nuance with operational constraints. Based in Oceanside, CA, he pairs academic rigor from UCSD bioengineering with practical impact in product and clinical environments.
EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD
Role in this project:
Back-end Developer
Contributions:17 commits, 11 PRs, 7 pushes in 2 years 8 months
Contributions summary:Clement primarily contributed to the EEGLAB project by modifying and updating various MATLAB functions related to EEG data processing. Their work involved enhancing electrode location functionalities, including adding and updating fiducial names and handling different file formats. They also addressed bugs and made improvements to GUI elements, such as the `pop_chanedit.m` and `pop_writelocs.m`, ensuring compatibility and preventing errors. Furthermore, the user updated dependencies and fixed issues related to data handling, displaying, and formatting.
Electrode localization using 3D head image. EEGLAB plug-in using Fieldtrip toolbox
Contributions:37 commits, 1 PR, 29 pushes in 3 years 10 months
3d-head3d-modelstoolboxheadplug-in
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