Yixin Tian [田毅鑫]

Hey! I'm Yixin ('Isshin'), a Computer Engineer and Data Scientist based in Toronto, Canada, developing human-centred AI systems at the intersection of Software Engineering and AI Research. My work focuses on advancing theoretical understanding and implementation across Human-AI Interaction, Multi-Agent Systems (MAS), Learning Science, Semantic Technologies, and MLOps.

Currently, I work as a Data Scientist at Royal Bank of Canada (RBC), where I focus on developing agentic AI assistants for the credit domain, leveraging DSPy, LangGraph, and tool-augmented LLMs. In the summer of 2025, I served as a team lead for RBC Amplify, mentoring a team of four to rapidly prototype an AI assistant for account managers using retrieval-augmented generation (RAG), text-to-SQL LLM agents, and automated client insight generation powered by anomaly detection. My previous experience spans deploying the open-source Dagster data orchestration platform, building event-driven inference and monitoring pipelines, and co-developing a patent-pending agriculture carbon-emission model into production.

Outside of work, I'm a part-time researcher at the University of Southern California's Information Sciences Institute (ISI), where I study structured data extraction (text-to-JSON) from long documents, knowledge graphs, and LLM agents.

My passion lies in exploring novel interaction paradigms for heterogeneous collaborative systems comprising both human and AI agents. By expanding the effective communication bandwidth within these networks, I aim to simultaneously augment human cognition and optimize multi-agent performance in real-world collaborative and educational settings. When I'm not building or researching, I enjoy running, writing (blogging + journaling), reading, and being with nature.