Area of research
Information Systems · Computational Theory and Mathematics
Research interest
Research interests include Petri Nets in System Modeling, Business Process Modeling and Analysis, Service-Oriented Architecture and Web Services, and Cloud Computing and Resource Management.
CamFD: Semi-Supervised Camouflage-Aware Fraud Detection Based on Dynamic Graphs
Heuristic-Guided Multi-Agent Reinforcement Learning for Computing Service Scheduling in Distributed Data Centers
Dynamic Min-Max Multi-Dimensional Reinforcement Backdoor Attacks and Orchestrated Closed-Loop Defense in Fairness-Aware Web Federated Finance
Along Came a Spider: Enabling Effective Cross-Domain Threat Detection via Collaborative Graph Learning
STG-DGR: Fraud Detection on Streaming Transaction Graphs with Diffusion-based Generative Replay
A Process Discovery for Endpoint-Level Call Relations in Microservice Systems
Layer-Adaptive-Augmentation-Based Graph Contrastive Learning With Feature Decorrelation
MGroup: Multi-Instance Workload Prediction Approach Based on Group Behavior Perception
Parse, Align and Aggregate: Graph-Driven Compositional Reasoning for Video Question Answering
MPGTrans: Semi-Supervised Misbehavior Detection with Multi-Path Graph Transformer for Internet of Vehicles
Exposing Disguises and Tracing Illicit Flows: Dual-View Graph Representation Learning for Money Laundering Detection
Beyond Graph Structure: Semantic Augmentation With LLMs for Bitcoin Money Laundering Detection Under Economic Networks
Privacy-Aware Transaction Fraud Detection With Low Communication Costs Under Joint Federated Learning
Binary-Encoding-Based Quantized Kalman Filter: An Approximate MMSE Approach
Multiscale Feature Fusion Transformer With Hybrid Attention for Insulator Defect Detection
Multi-Temporal Partitioned Graph Attention Networks for Financial Fraud Detection
Data-Free Knowledge Filtering and Distillation in Federated Learning
Parallel Graph Learning With Temporal Stamp Encoding for Fraudulent Transactions Detections
GLC++: Source-Free Universal Domain Adaptation Through Global-Local Clustering and Contrastive Affinity Learning
Financial Time Series Prediction With Multi-Granularity Graph Augmented Learning
Privacy Passport: Privacy-Preserving Cross-Domain Data Sharing
Meta Reinforcement Learning Based Adaptive and Interpretable Energy Storage Control Meets Dynamic Scenarios
HFTCRNet: Hierarchical Fusion Transformer for Interbank Credit Rating and Risk Assessment
Multi-View Graph-Based Hierarchical Representation Learning for Money Laundering Group Detection
Spreeze: High-Throughput Parallel Reinforcement Learning Framework
Dual Pairwise Pre-training and Prompt-tuning with Aligned Prototypes for Interbank Credit Rating
Federated Aggregation With Interlayer Personalized Contribution: Preference-Based Optimization Between Performance and Privacy
Model Checking of $\omega$-Independent Unbounded Petri Nets for an Unbounded System
Preferential Selective-Aware Graph Neural Network for Preventing Attacks in Interbank Credit Rating
Generative Dynamic Graph Representation Learning for Conspiracy Spoofing Detection