Background & Interests
I'm a junior ML engineer with a focus on machine learning, data processing, and systems programming. My work spans deep learning (GANs, VAEs), statistical data pipelines, network monitoring, and interactive data visualization. I enjoy building tools that turn raw data into actionable insight.
Technologies & Tools
Selected work from GitHub
GAN-based image generation extending MNIST architecture to CIFAR-10 color images. Tracks training progression across 50 epochs.
Comparative study of FC-VAE vs. Convolutional VAE architectures on CIFAR-10 & CelebA datasets with latent space interpolation.
Semi-supervised pipeline for fog/smog, rain, and sandstorm classification combining K-Means clustering with SVM and self-training.
Empirical study of chart type (bar, radar, donut) and color contrast effects on perceptual accuracy, with SurveyJS data collection.
Statistical profiling of 19 TPC-H queries on SQLite, capturing wall-clock time and memory usage across 10–40 runs per query.
Real-time BGP anomaly detection engine using dual-algorithm outlier detection (BLT-MAD + ShakeAlert) with a live web dashboard.