Yasir RashidOlapGN: locating influential nodes with a multi-layered graph convolutional network (opens in a new tab)
A multi-layered graph convolutional network built to locate the most influential nodes in a graph network.
Welcome
Hello, I'm Yasir Rashid.
I build graph neural network methods that find the most influential nodes in complex networks, and apply graph learning to healthcare and drug discovery.
Assistant Professor, Computer Science, Islamic University of Science and Technology, Kashmir
Published in
- Knowledge-Based Systems
- Multimedia Systems
- Multimedia Tools and Applications
- Indian Journal of Science and Technology
- NeuroQuantology
- Springer
What the research looks at
Online social networks form communities, and inside each one a few people hold the group together. My work builds graph neural network models that find those people automatically.
- Most influential user
- User
- Connection
- Colour: community
Selected work
All publicationsTopological, machine and deep learning approaches to influential node identification (opens in a new tab)
A systematic review of how influential users in social media networks are found, from topological measures to machine and deep learning.
Early detection of cardiovascular disease with machine and deep learning (opens in a new tab)
An experimental investigation of machine learning and deep learning techniques for detecting cardiovascular disease at an early stage.
Research areas
Read more- Graph neural networks and representation learningLearning from structure and node features to find influential nodes.
- Social network analysisInfluential users, community structure and overlapping communities.
- Drug discovery and biomedical applicationsGraph representations for computational drug discovery. Exploratory.
- Healthcare analyticsMachine and deep learning for disease prediction research.
Open to research collaboration
For research discussions, collaboration, student enquiries and correspondence.