I build machine-learning systems for search, recommendation, and AI agents.
My work spans retrieval, evaluation, and practical deployment.
I also enjoy turning what I learn into public talks, workshops, and reproducible projects.
A conversational music recommendation system that combines state extraction, multi-branch retrieval, rank fusion, learned reranking, and response generation.
Project site · Architecture walkthrough · Paper
An end-to-end retrieval and grounded-generation system, with accepted submission artifacts, architecture documentation, retrieval analysis, and citation-support evaluations.
Project site · Architecture report · Evaluation reports
A hands-on LangGraph workshop that builds a Deep Research workflow step by step through notebooks, slides, and sample reports.
- Building a Search Engine — PyData Seattle 2023
- Building a Semantic Search Engine — PyData NYC 2022
- Search Engine Workshop — notebooks and slides
- Improving Search Results Using Large Language Models — PyData Global 2023
- Improving Search Results Using RAG — workshop materials
- Serving PyTorch Models in Production — Data Umbrella 2022
- Serving PyTorch Models in Production — PyData NYC 2022
- Serving BERT Models with TorchServe — PyData Global 2021
- Deploying a Mobile App on TensorFlow — PyData Global 2021
- Training and Deploying TensorFlow Models at Scale — San Diego Machine Learning 2022
- PyTorch Serving Workshop — notebooks and slides