Projects
My research spans efficient knowledge graph retrieval, multi-agent clinical reasoning, and interpretable and robust anomaly detection.
Orchestrator-Centered Multi-Agent Systems for Clinical Reasoning
Specialized large language model agents generate, review, and refine diagnostic predictions through structured multi-step interactions, coordinated by a reinforcement-learning orchestrator.
BadSAD
Clean-label backdoor attacks against deep semi-supervised anomaly detection models.
LogosKG
Hardware-optimized, scalable, and interpretable multi-hop retrieval over large knowledge graphs.
BLOG
A backdoor attack framework designed for log anomaly detection models.
CFDet
Counterfactual explanations for sequence anomaly detection that identify minimal changes needed to convert an anomalous sequence into a normal one.
BA-OCAD
A clean-label backdoor attack framework targeting one-class sequential anomaly detection models.
EASD
Prototype-based explainable sequential anomaly detection with human-understandable explanations.
GLEAD
Sequential anomaly detection with both local explanations and global explanations.