Sho Nakagome
Full Time Dad at Meta
Redmond, Washington, United States
Summary
👤
Senior🎓
Top SchoolSho Nakagome is a neuroengineering researcher and applied machine learning practitioner with 11 years of experience building EEG-based Brain-Computer Interfaces and large-scale data pipelines. Currently a Research Scientist at Meta and a Ph.D. alum and former RA at the University of Houston’s Non-Invasive Brain Machine Interface Lab, he blends digital signal processing, state-space estimation (e.g., Kalman filtering), and deep learning to translate noisy neural and EMG signals into actionable interfaces. His industry internships at HP and Patchd gave him hands-on experience with Databricks/Spark, recommendation systems, and clinical early-warning modeling, demonstrating an ability to move research ideas into production-ready analytics. Sho’s long-term ambition is to create semi-invasive “Cyberbrain”-style BCI systems, and he pairs MRI/EEG source analysis skills with practical experience in large data ecosystems. Based in Redmond, WA, he uniquely combines academic rigor with product-oriented engineering at the intersection of neuroscience and HCI.
11 years of coding experience
Doctor of Philosophy (Ph.D.) Neuroengineering, Doctor of Philosophy (Ph.D.) Neuroengineering at University of HoustonBachelor of Engineering (B.E.) Bioengineering and Computer Science, Bachelor of Engineering (B.E.) Bioengineering and Computer Science at Keio University
English
Github Skills (19)
optimization10
reinforcement-learning9
parallel9
pytorch9
java9
python9
ray9
deep-learning8
hyperparameter-optimization8
tensorflow8
machine-learning8
llm8
scaling8
large-language-models8
automl8
Programming languages (2)
Github contributions (5)
shonaka/shoeeg
Mar 2017 - Sep 2018
Contributions:1 release, 65 commits, 83 pushes in 1 year 6 months
shonaka/pytorch_challenge
Dec 2018 - Dec 2018
Contributions:27 commits, 3 pushes in 18 days
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