About
I'm an Applied AI Engineer at C3 AI and a relentless AI enthusiast. Most of my work lives where applied research meets solid engineering: I take ideas from problem framing all the way to production, mostly RAG-based LLM systems and probabilistic time-series forecasting on C3's agentic platform.
I care about models that are interpretable, deployments that are reproducible, and tooling that makes the next person's work easier. Here is where I focus:
Experience
Lead applied ML and LLM projects end-to-end for global enterprises, currently an enterprise forecasting program for a major semiconductor customer with ~$0.8B estimated annual impact. Shipped a RAG document-retrieval system, demand and yield forecasting apps, and built an internal deployment toolchain that cut deploys from hours to minutes. I also mentor data scientists across teams.
Built an out-of-the-box hierarchical forecasting and reconciliation system (MinT/ERM, DeepVAR-Hierarchical) and added Integrated Gradients explainability to probabilistic forecasts.
Tree-based sales forecasting, a 95%+ accuracy image-similarity engine for product matching, and an order-management app that cut costs and stockouts.
Selected Work
From-scratch GANs, VAEs, and normalizing flows. A hands-on tour of how generative models actually work.
A clean implementation of visual attention / ViT for image classification.
A network-science study of academic co-authorship built on DBLP data. My most-starred repo.
An implementation and experimentation playground for diffusion-style generative models.
Skills & Tools
Education
MS, Computer Science · focus in Machine Learning
BE, Computer Science
Let's build something.
I'm always up for interesting problems and good conversations, whether that's a role, a collaboration, or just comparing notes on AI.
Say hello