WORKSHOP ON INTELLIGENT AGENTS IN SCIENCE AND ENGINEERING

In Conjunction with

22nd International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS'24) 

University of Salamanca, Spain

26th-28th June, 2024

ABOUT THE WORKSHOP


The objective of this multidisciplinary session is to gather both researchers and practitioners to discuss methodological, technical, organizational and environmental aspects of intelligent agents used across various application domains in science and engineering. The field of agents and multi-agent systems have received a significant amount of interest in recent years. These fields overlap strongly with many other areas in computer science, e.g. machine learning, artificial intelligence, computational modelling, etc. 

Agents and multi-agent systems have been successfully applied to many problem areas in science and engineering, e.g. modelling, simulation, decision making and control problems. This workshop will delve into various facets of intelligent agents, including their applications in scientific discovery, data analysis, optimization, and problem-solving within engineering domains. This workshop welcomes advances in agents research and also their application within the fields of science and engineering in both academia and industry. 

TOPICS

The workshop topics include (but are not limited to): 

- Renewable energy 

- Hardware 

- Robotics 

- Manufacturing 

- Natural sciences 

- Cloud computing 

- Smart grid 

- Biomedical science/engineering  

- Buildings and civil engineering broadly 

- Other application areas in science and engineering 

CALL FOR PAPERS

SUBMISSION DETAILS

DEADLINES

PUBLICATION DETAILS

WORKSHOP ORGANIZERS

Karl Mason

Karl Mason is a tenured Assistant Professor in the School Of Computer Science at University of Galway, Ireland. He is the PI on multiple projects and manages a research group of 11 funded researchers in Galway.  His research focuses on multi-agent systems, swarm intelligence, neural networks, evolutionary computing,and reinforcement learning, multi-agent systems. He is also interested in the application of machine learning methods to solve problems related to renewable energy, smart homes, infrastructure planning, smart grid, robotics, and agriculture.

Abdul Wahid

Abdul Wahid is a Postdoctoral Researcher at the School of Computer Science, University of Galway, Ireland. Prior to his appointment at Galway, he held positions as a Research Engineer at the UHA, France, and a Postdoctoral Fellow in the INFRES department at Telecom Paris, IP Paris, France. His research interests focus on AI, ML, and their applications in various domains. Apart from his research activities, he has organized a workshop on Artificial Intelligence for Sustainability (AI4S) at ECAI 2023 in Poland, and a workshop on Deep Learning for Sustainable Precision Agriculture (DLSPA) at ECML PKDD 2023 in Italy. 

Daniel Kelly

Daniel Kelly is a Postdoctoral Researcher at the School of Biomedical Engineering & CÚRAM at University of Galway, Ireland. His research aims to utilise Computer Vision for the autonomous correction of control parameters in extrusion-based 3D printing. His doctoral research focused on applying a novel means of translation of traffic logs into images for detection of a theoretical cyber-attack on Serverless Computing. He has also conducted prior research on the application of Computer Vision to Search and Rescue tasks such as casualty identification in ocean-based scenarios. Daniel’s interests lie in the application of Computer Vision and AI on novel physical systems, machine learning and additive manufacturing. 

Rachael Shaw

Dr. Rachael Shaw is a Lecturer in Information Systems in the School of Business at Atlantic Technological University (ATU). Rachael was awarded a scholarship from the Irish Research Council in 2016 and completed her PhD with the School of Computer Science at the University of Galway in 2020. Her research explored the application of Machine Learning and Artificial Intelligence techniques to optimize resource management systems and improve energy efficiency and performance in cloud computing environments. Her research focused on the proposal of novel resource management algorithms and decision support systems supported by predictive and statistical based methodologies. Rachael has achieved multiple national and international research successes, presenting her work in several leading international conferences and special issue journals. Rachael has also held various appointments on peer review panels including the European Conference on Artificial Intelligence (ECAI) and the Association for the Advancement of Artificial Intelligence (AAAI). Prior to completing her PhD, Rachael graduated from the University of Galway with a MSc in Software Design and Development. Rachael also holds a Bachelor’s Degree in Information Systems Management awarded by the ATU.

PROGRAM COMMITTEE

QUESTIONS?

All enquiries should be sent to the workshop organizers.