8th IEEE International Workshop on Advances in Artificial Intelligence and Machine Learning (AIML 2025): Futuristic AI and ML models & Intelligent Systems

The goal of the workshop

The goal of the workshop, eighth in the series at COMPSAC, is to foster interaction and information exchange among AI researchers and practitioners from academia and industry, on the safe, reliable and trustworthy application of Artificial Intelligence (AI) and Machine learning (ML) in real-world applications. 

The workshop aims at: presenting a variety of novel AI applications, case studies and large-scale validation of AI technologies; examining risks and concerns of AI and ML; outlining practical challenges in formulating an AI strategy; discussing AI for Good initiatives; AI & ML for better future; addressing topics such as explainable AI, algorithmic fairness, trust and reliability; and discussing challenges related to AI safe and robust deployment; AI on chip; new generation AI/ML models; Sustainable AI; AI for sustainability; testing/validation and certification; Generative AI; Ethical frameworks for AI; AI for sustainable growth; AI for sustainable supply chains; futuristic AI models; quantum ML models; Edge and tiny ML models.

Workshop theme

After decades of generous promises and frustrating disappointments, artificial intelligence (AI) is now delivering real-world benefits, and adopters in businesses and industry in different sectors are embracing the promise of AI, reaping significant benefits.  AI is now more pervasive and influencing all aspects of human life. The landscape of AI and ML is evolving beyond traditional supervised learning and deep neural networks, towards more sophisticated models capable of understanding and generating a richer range of information. The vision for the future of AI and ML revolves around building systems that are not only smarter but also more adaptive, autonomous, and capable of seamlessly interacting with their environments and humans. This futuristic AI and ML models promises to push the boundaries of what is possible, transforming industries, solving complex challenges, and enhancing the human experience.

This workshop seeks to explore the latest advancements in AI and Machine Learning models and their seamless integration into next-generation intelligent systems.  It aims to not only highlight the latest technological advancements but also to envision how these models and intelligent systems will shape industries, cities, and the fabric of everyday life. 

This year workshop is also aligned with COMPSAC 2025 theme, “Harnessing the power of Intelligent Systems: Shaping the future.”  

Scope of the workshop

This workshop will facilitate much needed interaction and information exchange among AI researchers, practitioners and business executives. It will provide an interactive forum for discussion on recent and ongoing developments, key issues and challenges, and practices related to AI applications. It will also serve as a platform to present case studies and discuss application to experience as well as to demonstrate applications and AI tools. Researchers and practitioners from all over the world, from academia, industry, and government will be invited to present their work and perspectives and participate in the workshop.  Participants will gain insights into the strategies and tools that will drive the development of AI and ML towards a more autonomous, adaptive, and ethically aware future.

Topics of interest include, but are not limited to: 

  • Advances in AI and machine learning, deep learning, cognitive computing, intelligent agent, chatbot 
  • AI strategy for business and industry 
  • AI applications in industry, business, healthcare, and education and training 
  • AI in the fight against pandemics. 
  • AI in government 
  • AI for social good 
  • AI in legal practice, and legal aspects of AI (liability, etc) 
  • AI for enhancing information security and privacy 
  • Work in the age of AI 
  • Trust, resilience, privacy and security issues in AI applications 
  • Testing and validation of AI and ML applications 
  • Risks, limitations, and challenges of AI and ML 
  • Legal, regulatory, ethical aspects of AI 
  • AI: promise vs practice 
  • Societal implications of the rise of AI 
  • AI and blockchain 
  • Human-centered AI 
  • Explainable AI 
  • Responsible AI 
  • Trustworthy AI 
  • Human-machine co-existence and collaboration 
  • Intelligent, autonomous robots and cars 
  • Industry 4.0 
  • Smart society 
  • AI and IoT 
  • Case studies, experience reports, lessons learned 
  • Overview of AI activities in a region/country 
  • The Future of AI 
  • Adversarial ML & Deep Fakes
  • Secure AI models
  • Scalability of ML models
  • Lightweight ML models / ML for edge devices
  • Quantum ML
  • AI for Sustainable development goals.
  • Generative AI
  • AI for better and sustainable future
  • AI based precision agriculture
  • AI for greener future
  • AI for sustainable supply chains
  • AI for sustainable resource use
  • AutoML models
  • Casual ML models
  • Self-repairing and resilient intelligent systems

Workshop organizer(s)

Aswani Kumar Cherukuri
Vellore Institute of Technology, India
Email: cherukuri@acm.org

San Murugesan
BRITE Professional Services, Australia
Email: san1@internode.net

Arghya Kusum Das
University of Alaska Fairbanks, USA
Email: akdas@alaska.edu

Program Committee

Antonio Vetrò
Politecnico di Torino, Italy

Ashraf Elnagar
University of Sharjah, Arab Emirates

Darshika G. Perera
University of Colorado, USA

Debasis Ganguly
University of Glasgow, United Kingdom

Firuz Kamalov
Canadian University Dubai, UAE

Gang Li
Deakin University, Australia

Gianfranco Politano
Politecnico di Torino, Italy

Ivan Donadello
Libera Università di Bolzano, Italy

Jan Hidders
Birkbeck University of London, United Kingdom

Jinhai Li
Kunming University of Science and Technology, China

Juan A. Álvarez-García
University of Seville, Spain

Kenichi Yoshida
Tsukuba University, Japan

Kozo Ohara
Aoyama Gakuin University, Japan

Lia Morra
Politecnico di Torino, Italy

Luigi Troiano
University of Salerno, Italy

Maria R. Lee
Shih Chien University, Taiwan

Michael Eiden
Arthur D Little, UK

Min Xu
Carnegie Mellon University, USA

Mohan K
Bavirisetty, CISCO, USA

Mufti Mahmud
Nottingham Trent University, United Kingdom

Muhammad Naveed Aman
University of Nebraska-Lincoln, USA

Paula Brito
Universidade do Porto, Portugal

Praveen Kumar Donta
Vienna University of Technology, Austria

Sambit Bakshi
NIT Rourkela, India

Santosh Kumar Ray
Khawarizmi International College, UAE

Saqib Hakak
University of New Brunswick, Canada

Shalini Kurapati
Clearbox AI, Italy

Shaoshan Liu
PerceptIn, USA

Silvia Delsanto
Jato Dynamics, Italy

Sriram Chellappan
University of South Florida, USA

Sydney Kasongo
Stellenbosch University, South Africa

Tad Gonsalves
Sophia University, Japan

Tania Cerquitelli
Politecnico di Torino, Italy

Tran Duc Tan
Phenikaa University, Vietnam

Uttam Ghosh
Vanderbilt University, USA

Vijayalakshmi Saravanan
University of South Dakota, USA

Voliansky Roman
National Technical University, Ukraine

Xiaolong Zheng
Institute of Automation Chinese Academy of Sciences, China

Yulei Wu
University of Exeter, United Kingdom

Yunji Liang
Northwestern Polytechnical University, P.R.China

Yuriy Dyachenko
Ukranian National University, Ukraine

Important Dates

UPDATED: Full symposium papers due
January 31, February 15, February 28, 2025

Symposium paper notification
April 7, 2025

Workshop papers due
April 15, 2025

Workshop papers notification
May 1, 2025

Camera-ready copy
June 1, 2025

Conference Dates
July 8-11, 2025

Paper Templates

IEEE Paper templates are available in MS Word 2003 and LaTex. All submissions must use US 8.5×11 letter page format.

IEEE Conference Publishing Policies

All submissions must adhere to IEEE Conference Publishing Policies.

IEEE Cross Check

All submission will be screened for plagiarized material through the IEEE Cross Check portal.