Agentic AI β multi-agent systems on MCP that investigate, reason, and act
LLM β RLHF / alignment, RAG, tool-use, agent orchestration
Fraud & Risk β anomaly detection, feature attribution, human-in-the-loop review
RecSys β deep CTR ranking, multi-objective, two-tower retrieval
Iβm currently researching in-context learning with Claude Fable, building multi-agent fraud investigation systems, and chasing a few other ambitious ideas at the edge of agents and large-scale ML β self-improving pipelines, LLM-as-investigator workflows, and autonomous research agents. Lately Iβve also been vibe-coding 3D games for fun.
Cornell University β Computing & Information Science Β· @CornellCIS
Nanjing University β LAMDA Lab Β· @LAMDA-NJU
From large-scale RecSys & risk systems to LLM agents that reason and act.

