Thème :
Current Research Directions
Présentation :
Axis 1: Graph Neural Networks for Recommendation and Social Systems, Community-Based Recommendation, interest networks , temporal dynamics of interests
Axis 2. Relational Deep Learning and Knowledge Graphs
Axis 3. Graph Learning for Bioinformatics and Healthcare, Diagnosis and therapeutic effects of drugs using GNNs architectures, Genomic Data Analysis, Microbiome dynamics, Knowledge extraction structured information from unstructured Medical Text
Axis 4. Graph Learning for Environmental Systems to predict phenomena in complex spatial and temporal systems.
Axis 5. Combine natural language processing and graph learning for richer text understanding. and Sentiments Analysis
Thème :
Broad Research Interests
Présentation :
- Data and Graph Mining
- Complex Networks
- Social Network Analysis and Mining
- Computational Social Networks, Collaboration Networks, and Social E-Learning
- Web-Based Communities, Learning Communities, and Communities of Interest
- Machine Learning
- Community Detection
- Dynamic Social Networks
- Group Dynamics
- Underlying Structure and Pattern Detection
- Semantic Communities
- Semantic Web
- Graph Neural Networks
- Recommender Systems
- Sentiment Analysis
- Machine and Deep Learning for Healthcare, Genomics, and Complex Disease Diagnosis
- Applications of Graph Neural Networks in Bioinformatics
- Relational Deep Learning and Generative AI