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Generative Artificial Intelligence


Generative Artificial Intelligence, Gen AI or GAI for short, is a rather new topic in the field of artificial intelligence and machine learning. GAI enables users to create synthetic but realistic documents. This short course is designed to equip participants with fundamental knowledge in GAI. Tailored for individuals with military backgrounds, this course provides an accessible introduction to key concepts and applications of generative AI. Participants will explore techniques for generating realistic data, images, and text using algorithms such as generative adversarial networks (GANs) and variational autoencoders (VAEs). Through hands-on exercises and real-world examples, participants will gain practical insights into how generative AI can enhance military operations, from synthetic training data generation to scenario planning and decision support systems.

Learning Outcome

(1) Demystification of Generative AI via valid and updated knowledge transfer.

(2) Exploration of Generative Techniques for participants.

(3) Understanding general applications of GAI.

(4) Understanding military Applications of GAI.

(5) Cultivating ethical awareness and limitations of GAI.

(6) Hands-on experimentations.

Trainer Bio

Senior Lecturer, School of Computing<br>National University of Singapore Dr Amirhassan Monajemi

Dr Amirhassan Monajemi

Senior Lecturer, School of Computing
National University of Singapore

Dr Amirhassan Monajemi is a Senior Lecturer at the School of Computing, National University of Singapore (NUS). Before joining the NUS, he was with the Faculty of Computer Engineering, University of Isfahan, Iran, where he was serving as a professor of AI, Machine Learning, and Data Science. He was born in 1968 in Isfahan, Iran. He studied towards BSc and MSc in Computer Engineering at Isfahan University of Technology (IUT), and Shiraz University, both in Iran, respectively. He got his PhD in computer engineering, pattern recognition and image processing, from the University of Bristol, Bristol, England, in 2005. His research interests include AI, Machine Learning, Machine Vision, IoT, Data Science, and their applications. He has taught artificial intelligence courses, including AI, Machine Learning, Computer Vision, Expert Systems, and Neural Networks and Deep Learning since 2005 at both undergraduate and postgraduate levels. He was awarded the best university teacher of the province in 2012. He also has studied, E-Learning and E-Learning for workplaces since 2007. Dr. Monajemi has registered a few patents in the fields of AI, Machine Vision, and Signal Processing applications, including an AI and machine vision-based driver drowsiness detection system and a low power-consuming spherical robot. He also has published more than a hundred research papers in peer-reviewed journals and international conferences and supervised several Data Science, IoT, and AI industrial projects on various scales, including Isfahan intelligent traffic system delivery and testing and red-light runners detection. He is experienced in different sub-domains of Artificial Intelligence and Machine Learning, from theory to practice, including Deep Learning, Logic, and Optimisation.


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