My work spans NLP, Large Language Models, generative AI, and multi-agent systems, with a focus on building reliable and evaluable solutions.

In industry, I develop NLP pipelines, tooling, and analyses that translate models into measurable outcomes. In research, I design agentic AI workflows for reasoning, summarization, and understanding. I also maintain open-source research projects, including BioNeuralNet, a graph neural network toolkit for multi-omics network representation and downstream tasks. I combine ML and DL, graph neural networks, multimodal learning, and full-stack engineering to move ideas into production and practice.