Blogs
Essays, technical walkthroughs, and course reviews at the intersection of computational neuroscience and machine learning. Some posts are code-driven with interactive demos, while others are reflective write-ups meant to help readers quickly orient to a topic.
Denoising Images with Natural Scene Statistics
Published: April 25, 2026
A walkthrough of image denoising and inpainting using simple priors over natural images.
The post starts with Fourier intuition and the 1/f2 power spectrum, then uses
Bayesian inference, Wiener filtering, wavelet coring with steerable pyramids, Langevin
sampling, and missing-pixel reconstruction.
VS 265 (Neural Computation): Course Review
Published: January 1, 2026
A concise review of UC Berkeley's VS 265, covering course structure, lecture themes,
assignments, projects, and why it is a strong entry point for students interested in
computational neuroscience and NeuroAI.
UC Berkeley's Machine Learning Curriculum Review
Published: November 20, 2022
A chronological review of Berkeley ML-related coursework with context on course
sequencing and reflections on the overall educational experience.