Hi 👋, I am Yuan Tian. I'm currently a Ph.D. candidate in the Department of Computer Science at Purdue University, advised by Professor Tianyi Zhang.
My research focuses on agentic data system, where I build coding and database agents for data-intensive tasksData-Intensive Tasks
Such tasks often involve overwhelming amounts of context (e.g., millions of data records), which is
challenging for agents to consume and process.. My work spans two complementary directions:
- Agent-centric: designing and scaling the interaction between AI agents and data environments via different approaches, such as post-training, attention steeringInspired by the anchoring effect, flexibly steering attention to the most relevant context, overcoming attention dilution, making generation more controllable and accurate., scaffoldingInspired by the grounding theory, scaffolding and decomposing the generation into mutiple accessible feedback loops (common ground), reducing task complexity, isolating errors, and improving performance., reasoning and verification.
- Data-centric: building data pipelines via programmatic data synthesis and augmentation for domain adaptation, as well as semantic enrichment to enhance the quality of data environments.
Besides my research, I am working on an
NSF project
, where I am building an ontology-driven knowledge
graph for AI security [Demo].
I interned twice at
Adobe
as an applied scientist, where I mainly worked on the
AI
assistant for Adobe
Experience Platform.
📢 I'm seeking full-time AI research positions. Feel free to contact me at tian211@purdue.edu. Thank you!
Data
