Blog
Notes on generative AI, anomaly detection, benchmarking, and the occasional math.
Demystifying Variational Autoencoders (VAEs): From Variational Inference to Deep Generative Models
A from-scratch walkthrough of the math behind VAEs — from ELBO and KL divergence to the reparameterization trick — explained the way I wish someone had explained it to me.
2024-11-20 · 2 min readAI-Sciantist: An Autonomous Research Loop That Never Sleeps
I built a closed-loop AI research system that ideates, implements, trains, evaluates, and iterates on ML experiments — with 8 expert personas, HPC cluster integration, and live human steering.
2024-09-15 · 2 min readPaper Reader: Listening to Science, One Word at a Time
How I built a web app that reads scientific papers aloud with word-level highlighting, converts LaTeX math to spoken English, and runs on Kubernetes with neural TTS.
2024-06-19 · 2 min readVariational Autoencoders for Anomaly Detection: A Gentle Introduction
A walkthrough of how variational autoencoders can be used for unsupervised anomaly detection, with the math behind the ELBO and reconstruction-based scoring.
2024-03-10 · 1 min readRunning the MOOD Challenge: Lessons from 80+ Teams
Five years of organizing an international anomaly detection benchmark taught me a lot about fair evaluation, Docker-based submissions, and what really matters in medical AI.