Pablo Damasceno is an Associate Director of Data Science R&D with seven years of experience translating advanced machine learning and computational modeling into clinical and industrial impact. He combines a PhD in Applied Physics with postdoctoral work at UCSF to lead interdisciplinary projects across neuroimaging, digital health time-series, and molecular simulation, moving algorithms from research prototypes into robust pipelines. At Johnson & Johnson he progressed rapidly through senior scientific roles, driving R&D strategy and production-ready analytics, while earlier academic work delivered MCMC and deep learning methods for brain-state and disease modeling. He also contributes to open-source infrastructure, improving CI/CD for high-profile projects like Streamlabs Desktop, reflecting a practical focus on reproducible, deployable systems. Colleagues rely on him for bridging rigorous quantitative research with engineering best practices and stakeholder-facing translational outcomes.
7 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD Engineering Physics/Applied Physics, Doctor of Philosophy - PhD Engineering Physics/Applied Physics at University of Michigan
Visiting Scholar Chemistry, Visiting Scholar Chemistry at University of Cambridge
Bachelor’s Degree Physics, Bachelor’s Degree Physics at UFSCar - Alumni
Postdoctoral Scholar Radiology and Biomedical Imaging, Postdoctoral Scholar Radiology and Biomedical Imaging at University of California, San Francisco
Free and open source streaming software built on OBS and Electron.
Role in this project:
DevOps Engineer
Contributions:9 commits, 10 PRs, 13 pushes in 1 year 1 month
Contributions summary:Pablo primarily focused on improving the continuous integration (CI) process for the `streamlabs/desktop` repository. Their contributions involved adding and configuring tools within the CI pipeline, including Visual Studio Build Tools, CMake, and 7zip. They also modified the CI scripts to correctly handle Azure agent setup and file management, demonstrating a focus on automating build and deployment processes. Furthermore, the user integrated Visual Studio 2019 Build Tools.
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Pablo Damasceno - Associate Director, Data Science R&D