Alexander Belsten
PHD Candidate
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolAlexander Belsten is a postdoctoral researcher at UC Berkeley with eight years of experience at the intersection of computational engineering and neuroscience, currently advancing theoretical vision science at the Redwood Center. Trained as a computer and systems engineer at Rensselaer Polytechnic Institute and a PhD candidate at Berkeley, he blends quantitative modeling, neural data analysis, and systems-level thinking to probe visual processing. His background includes multi-institutional research roles—from neurosurgery labs at Washington University to adaptive neurotechnology at NCAN—revealing a knack for translating clinical and experimental challenges into computational hypotheses. Known for rigorous, reproducible research practices, he applies engineering discipline to complex neural datasets and experimental design. Based in Berkeley, he brings both hands-on algorithmic skills and a deep understanding of biological constraints to theoretical and applied problems in vision neuroscience.
8 years of coding experience
Doctor of Philosophy - PhD, Vision Science, Doctor of Philosophy - PhD, Vision Science at University of California, BerkeleyBachelor's degree, Computer and Systems Engineering, Bachelor's degree, Computer and Systems Engineering at Rensselaer Polytechnic Institute
Github Skills (5)
react9
sparse9
inference6
machine-learning6
jekyll5
Programming languages (3)
Github contributions (5)
rctn/sparsecoding
Feb 2022 - Jun 2022
Reference sparse coding implementations for efficient learning and inference.
Contributions:25 reviews, 90 commits, 44 PRs in 3 months
implementationsinferencesparsemachine-learningsparse-coding
belsten/belsten.github.io
Jul 2020 - Feb 2025
Personal Website from github Pages
Contributions:6 PRs, 100 pushes, 1 branch in 4 years 8 months
jekyll
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