Membership Review and Selection Process
Celebrating our members and volunteers in engineering for a better world for us all.
At ICAEIC, membership is treated as a mark of professional distinction. Admission is not automatic and is not granted solely on the basis of application submission. Each application is considered through a structured screening process designed to protect the quality, integrity, and international standing of the society.
Because ICAEIC represents the International Council for Advanced Engineering Innovations and Computing, the evaluation of new members is conducted with seriousness and care. Applications may be reviewed against academic background, research profile, industry contribution, technical expertise, professional ethics, leadership experience, interdisciplinary impact, and relevance to advanced engineering and computing.
Only applicants who demonstrate meaningful expertise, professional credibility, and alignment with the mission of ICAEIC should be considered for admission. The society seeks members who have made notable contributions in engineering, artificial intelligence, robotics, computing, data science, automation, intelligent systems, or closely related technical domains.
High-Screening Membership Policy
ICAEIC follows a high-screening membership approach in order to preserve the prestige of the society and ensure that membership remains a respected professional recognition.
Under this process, applicants may be assessed on the basis of:
- Academic qualifications and institutional standing
- Research achievements and publications
- Technical innovation and real-world contribution
- Professional and industry impact
- Evidence of leadership, service, or mentorship
- Ethical conduct and professional reputation
- Alignment with ICAEIC’s values and objectives
Review Timeline
Membership review is conducted carefully and may take time. Depending on the applicant’s profile, field of expertise, and the need for verification, the review period may extend over several weeks.
Applicants are therefore requested to submit accurate and complete information at the time of application. Incomplete, inconsistent, or unverifiable submissions may lead to delay, deferral, or rejection.
Standard Expected from New Members
ICAEIC welcomes professionals, researchers, innovators, and academic leaders who demonstrate genuine excellence in their area of work. New members are expected to bring depth of knowledge, professional maturity, and a commitment to advancing engineering and computing for the broader global good.
Membership is especially intended for individuals who show one or more of the following:
- Recognised expertise in an advanced technical field
- A strong scholarly, research, or innovation record
- Meaningful professional achievements in academia or industry
- Demonstrated contribution to engineering, AI, robotics, computing, or interdisciplinary science
- Commitment to ethics, professionalism, and knowledge-sharing
International Academic and Technical Review Support
To maintain high standards, ICAEIC may seek input from senior academic and technical experts from internationally recognised institutions when appropriate. Such consultation helps strengthen the fairness, credibility, and global relevance of the membership review process.
Important note: Individuals should only be listed publicly on the website after formal confirmation of their role and consent to be named.
Final Decision
All membership decisions are made after internal review and quality screening in accordance with ICAEIC standards. The final outcome may be approval, request for clarification, deferred review, or non-acceptance, depending on the strength and completeness of the application.
ICAEIC remains committed to building a credible and distinguished international community of experts in advanced engineering innovations and computing.
Advisory committee for ICAEIC:
- Wolfram Burgard, Professor of Artificial Intelligence and Robotics, University of Technology Nuremberg, Germany.
- Virginia Dignum, Associate Professor in Social Artificial Intelligence, Delft University of Technology, Netherlands.
- Jens Kober, Associate Professor in the Cognitive Robotics department, Delft University of Technology, Netherlands.
- Pieter Abbeel, Professor in Artificial Intelligence and Robotics, University of California, Berkeley.
- Stuart Russell, Professor of Computer Science, University of California, Berkeley, with research in artificial intelligence and machine learning.
- Julie A. Adams, Professor at Oregon State University, working in distributed AI, robotics, and human-robot interaction.
- Alan Fern, Professor of computer science, artificial intelligence, and robotics at Oregon State University.
- Animesh Garg, Assistant Professor at Georgia Tech, leading the People, AI, and Robotics group.
- Sethu Vijayakumar, Professor of Robotics, University of Edinburgh.
- Subramanian Ramamoorthy, Professor of Robot Learning and Autonomy, University of Edinburgh.
- Michael Rovatsos, Professor of Artificial Intelligence, University of Edinburgh.
- Stefano V. Albrecht, Lecturer in the School of Informatics, University of Edinburgh, working on autonomous agents, multi-agent systems, and reinforcement learning.
- Teng Joon (TJ) Lim, Professor in the School of Electrical and Computer Engineering, University of Sydney.
- Chang Xu, Associate Professor in Machine Learning and Computer Vision, University of Sydney.
- Ian Abraham, Academic in robotics, optimisation, control, machine learning, and AI at the University of Sydney School of Electrical and Computer Engineering.
- Shuaiwen Song, Associate Professor in the School of Computer Science, University of Sydney.
- Chiranjib Bhattacharyya, Professor, Computer Science and Automation, Indian Institute of Science
- Jie Lu, Distinguished Professor, University of Technology Sydney, leading the Australian Artificial Intelligence Institute.
- Simon Lucey, Professor of Artificial Intelligence and Director of the Australian Institute for Machine Learning, Adelaide University.
- Brendan McCane, Professor, University of Otago; works in computer vision, pattern recognition, machine learning, biomedical imaging, and robotics.
- Albert Bifet, Professor of AI and Director of the AI Institute, University of Waikato.
- Bernhard Pfahringer, Professor and Co-Director of the AI Institute, University of Waikato.
- Andrew McDaid, Associate Professor, University of Auckland; works on rehabilitation robotics, wearables, AI, machine learning, and intelligent adaptive control.
Memberships issues in 2025:
- Daniel Meyer – Student
- Clara Hoffman – Student
- Matteo Ricci – Student
- Sofia Laurent – Student
- Lucas Vermeer – Student
- Emily Carter – Student
- Nathan Brooks – Student
- Olivia Bennett – Student
- Liam Anderson – Student
- Hannah Fischer – Student
- Erik Lindberg – Student
- Marta Novak – Student
- Thomas Keller – Student
- Isabelle Martin – Student
- Adrian Schmidt – Student
- Elena Romano – Student
- Victor Dubois – Student
- Julia Schneider – Student
- Marcus Wilson – Student
- Anna Kowalski – Student
- Peter Jensen – Student
- Laura Moretti – Student
- Kevin Mitchell – Student
- Emma Collins – Student
- David Clarke – Student
- Nicolas Weber – Associate
- Rachel Turner – Associate
- Simon Walsh – Associate
- Gabriel Costa – Associate
- Nina Petersen – Associate
- Felix Wagner – Associate
- Michael Edwards – Member
- Jonathan Reed – Member
- Patrick Sullivan – Member
- Andrew Morgan – Member
- Christopher Hayes – Member
- Robert Mason – Member
- Stephen Cooper – Technician Member
- Martin Hughes – Technician Member
- Alex Bennett – Apprentice
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