Technical Workshop Series
GRAPH NEURAL NETWORKS (GNNS) FOR LINK PREDICTION
(Unveiling the Power of Graphs in Predicting Connections) (1st Offering)
Presenter: Nahid Abdolrahmanpour
Date: Thursday, July 25, 2024
Time: 10:00 am
Location: 4th Floor at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)
Abstract:
Graph Neural Networks (GNNs) have emerged as powerful tools for analyzing and predicting connections in complex systems represented as graphs. This workshop will provide a comprehensive introduction to GNNs and focus on their application in link prediction. The workshop aims to empower attendees with the knowledge and skills needed to leverage the potential of GNNs in uncovering hidden relationships within graph-structured data.
Workshop Outline:
1. Introduction to Graphs and Link Prediction
2.Fundamentals of Graph Neural Networks (GNNs)
3. Data Preparation for Link Prediction
4. Building a Graph Neural Network Model
5. Link Prediction with GNNs
6. Q&A and Discussion
Prerequisites:
- Basic understanding of machine learning concepts
- Knowledge of basic graph theory (nodes, edges, connectivity)
- Prior exposure to neural networks is beneficial but not mandatory
Biography:
Nahid Abdolrahmanpour (Ph.D. Student in Computer Science) at the University of Windsor, With a solid foundation in Data Mining and Artificial Intelligence.
Research Focus: Social Network Analysis
She has previously earned a master's degree in computer science, specializing in Data Mining.
MAC STUDENTS ONLY - Register here
Reminder: Workshops marked as 1st Offering and 2nd Offering mean the exact same workshop is running at two different times - DO NOT REGISTER FOR BOTH. Students will not get points for attending the same workshop twice.