Area of research
Signal Processing · Computer Networks and Communications
Research interest
Research interests include Computer science, Scalability, Fraction (chemistry), Vertex (graph theory), Parallel computing, and Graph.
T-FSM: A Scalable Distributed Task-Based System for Frequent Subgraph Pattern Mining from a Big Graph
FELight: Fairness-Aware Traffic Signal Control via Sample-Efficient Reinforcement Learning
PCA-UNET for Object Segmentation
T-FSM: A Task-Based System for Massively Parallel Frequent Subgraph Pattern Mining from a Big Graph
HRL4EC: Hierarchical reinforcement learning for multi-mode epidemic control
Fraction-Score: A Generalized Support Measure for Weighted and Maximal Co-Location Pattern Mining
Efficient Algorithms for Maximal k-Biplex Enumeration
Maximal Directed Quasi -Clique Mining
Aspect-Aware Graph Attention Network for Heterogeneous Information Networks
A Study of Shape Modeling Against Noise
Towards advancing the earthquake forecasting by machine learning of satellite data
Predicting Autism Spectrum Disorder from Brain Imaging Data by Graph Convolutional Network
Learning to Generate Maps from Trajectories
Fraction-Score: A New Support Measure for Co-location Pattern Mining
On optimal worst-case matching