Area of research
Artificial Intelligence · Signal Processing
Research interest
Research interests include Computer science, Graph, Differential privacy, Maximization, PageRank, and Theoretical computer science.
Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs
Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System
PANE: scalable and effective attributed network embedding
Data synthesis via differentially private markov random fields
LF-GDPR: A Framework for Estimating Graph Metrics With Local Differential Privacy
The Disruptions of 5G on Data-Driven Technologies and Applications
Homogeneous network embedding for massive graphs via reweighted personalized PageRank
GPU-Accelerated Subgraph Enumeration on Partitioned Graphs
Efficient approximation algorithms for adaptive influence maximization
Analyzing Subgraph Statistics from Extended Local Views with Decentralized Differential Privacy
Privacy Enhanced Matrix Factorization for Recommendation with Local Differential Privacy
Online Processing Algorithms for Influence Maximization
PrivTrie: Effective Frequent Term Discovery under Local Differential Privacy
Skyline Community Search in Multi-valued Networks
Efficient algorithms for adaptive influence maximization
Efficient Route Planning on Public Transportation Networks
Secure nearest neighbor revisited
Shortest path and distance queries on road networks
Shortest path and distance queries on road networks