# Tutorial 1
Title : Graph Neural Networks: From Zero to Hero
9
th
of February 2025 8.30 AM - 11.30 AM
Abstract
This tutorial introduces Sri Lankan researchers to the foundational concepts, advanced methodologies, and practical applications of Graph Neural Networks (GNNs). The tutorial spans eight modules, covering basics like graph theory and linear algebra, advanced GNN architectures such as Graph Convolutional Networks (GCNs) and Graph Attention Networks (GATs), and hands-on sessions using PyTorch Geometric (PyG).Resource Persons
Dr. Dharshana kasthurirathna
Department of Computer Science, Faculty of Computing, SLIIT
Dr. Mahima Weerasinghe
Department of Computer Science, Faculty of Computing, SLIIT
Dr. Dinuka Sahabandu
Department of Computer Science, Faculty of Computing, SLIIT
Mr. Jeewaka Perera
Department of Computer Science, Faculty of Computing, SLIIT
Mr. Asiri Gawesha
Department of Software Engineering, Faculty of Computing, SLIIT
Mr. Sanka Mohottala
Department of Computer Science, Faculty of Computing, SLIIT
# Tutorial 2
Title : AI Enabled NextG Wireless and IoT for a Fully Connected Smart World
10
th
of February 2025 8.30 AM - 11.30 AM
Abstract
This tutorial explores the transformative role of Artificial Intelligence (AI) and next-generation wireless communication systems in building a fully connected world using Internet of Things (IoT).Resource Persons
Dr. Mayur Katwe
Department of Electrical and Computer Engineering, NIT Raipur, India
Dr. Himal A. Suraweera
Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Peradeniya
Prof. Maheshi B. Dissanayake
Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Peradeniya
Dr. Sampath Edirisinghe
Department of Computer Engineering, Faculty of Engineering, University of Sri Jayewardenepura
# Tutorial 3
Title : Machine Learning for Next-Generation IoT Applications
11
th
of February 2025 8.30 AM - 11.30 AM
Abstract
This tutorial will cover the fundamentals, methodologies, applications, and future research directions for using ML in IoT systems. Moreover, there will be a hands-on session focused on ML for wireless indoor localization, addressing the fundamentals of these technologies, signal processing techniques, ML algorithms for localization, and the practical implementation of models using Python.Resource Persons
Prof. Attaphongse Taparugssanagorn
Department of Information and Communications Technologies, Asian Institute of Technology, Thailand
Dr. MWP Maduranga
Centre for Telecommunication Research (CTR), Sri Lanka Technology Campus (SLTC), Padukka, Sri Lanka
Eng. Isuru Lakmal
Department of Mechatronics & Industrial Engineering,Faculty of Engineering, NSBM Green University, Sri Lanka