Things I have built

Code that actually runs. Most of these started as coursework or side projects and turned into something worth sharing.

Generative modeling

Diffusion · PyTorch · Sampling · FID

Variance-Preserving Diffusion for Image Generation

A VP diffusion model written from scratch: custom noise schedules, forward/reverse processes, and few-step sampling with NFE 1, 2, and 4.

Compared consistency-model and ReFlow-style shortcuts to see what actually lowers FID when you only get a handful of function evaluations.

Open repository

Computational neuroscience

Wilson-Cowan · Dynamical systems · Stochastic processes

Stress, Delay & Noise in Gamma-band Oscillations

A Wilson-Cowan circuit that shows how tonic drive, feedback delay, and noise reshape cortical rhythms.

The surprising result: moderate noise increases coherence. The model also reproduces gamma-to-beta shifts seen in stressed cortex.

Open repository

Applied ML

Computer vision · YOLOv8 · CLI · OpenCV

Real-Time Object Counting (YOLOv8 + OpenCV)

A CLI that counts objects in images, video files, YouTube links, or a live webcam feed.

Modular enough to swap detectors. Tuned to run on CPU (macOS) without feeling slow.

Open repository

More explorations

Generative modeling

Diffusion Image Generation Challenge

Pitted diffusion against flow-based methods to see which generates better images in under four sampling steps.

Most of the gains came from scheduler design and denoising tricks, not architecture changes.

Diffusion · Flows · Image synthesis

Open repository

ML foundations

ML & Generative Modeling Notebooks

End-to-end experiments: data splits, bias-variance, logistic regression, feedforward nets, neural ODEs, and denoising score matching.

Every notebook is self-contained and designed to be re-run without setup pain.

ML pipelines · Neural ODEs · Statistics

Open repository

Biological modeling

Mathematical Biology Mini-Projects

ODE models, parameter estimation, clinical stats, and single-cell analysis across several small projects.

Mixed dynamical systems with dimensionality reduction (PCA, t-SNE, UMAP) to make sense of real data.

ODEs · Optimization · Single-cell data

Open repository

Theoretical neuroscience

Neural Dynamics & Information Processing

Neuron models, spike train analysis, STDP, and information-theoretic views of how neurons encode signals.

The point was to explain behavior with simple models, not just fit outputs.

Neural coding · STDP · Simulation

Open repository