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INFUS 2027: International Conference on Intelligent and Fuzzy Systems

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Submission Date:
2027-02-15 Due in 163 days
Notification Date:
2027-03-15
Conference Date:
2027-07-27
Location:
Cappadocia, Turkey
Years:
Viewed: 14374   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

40.5 / 100
Ranked #4,918 of 5,650 conferences · Top 88%

#620 of 735 in Artificial Intelligence & Machine Learning

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
19
Community attention (10%)
10
Public record completeness (15%)
55

Inputs used: Editions on record: 1 · Researchers who opened this page in the past 24 months: 3

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-05

Call For Papers

INFUS 2027 (International Conference on Intelligent and Fuzzy Systems) is an academic conference held in Cappadocia, Turkey on 2027-07-27. The paper submission deadline is 2027-02-15. Acceptance notifications are sent on 2027-03-15.

INFUS 2027 Conference Theme “Trustworthy and explainable Intelligence for Sustainable and Resilient Systems” The rapid development of artificial intelligence is transforming the way complex systems are designed, operated, and managed. However, intelligent systems must not only be powerful and accurate, but also trustworthy, transparent, and understandable. The theme “Trustworthy and Explainable Intelligence for Sustainable and Resilient Systems” emphasizes the development of intelligent technologies that can support reliable decision-making in uncertain and dynamic environments. Explainable artificial intelligence can help users understand why a system produces a particular prediction, recommendation, or decision. Trustworthiness further requires intelligent systems to be robust, secure, fair, ethical, and accountable. These characteristics are particularly important in critical applications such as healthcare, energy, transportation, manufacturing, finance, and environmental management. Sustainability calls for intelligent solutions that use resources efficiently while contributing to long-term economic, environmental, and social well-being. Resilience, meanwhile, requires systems to anticipate disruptions, adapt to changing conditions, and recover effectively from unexpected events. Fuzzy systems, machine learning, evolutionary computation, and other computational intelligence approaches offer valuable tools for addressing these challenges. Combining these approaches can enable intelligent systems to reason under uncertainty while remaining interpretable and adaptable. The integration of human knowledge with data-driven intelligence can also improve both the reliability and practical acceptance of intelligent solutions. Such systems should place humans at the center of decision-making rather than treating intelligence as a replacement for human judgment. Researchers are therefore encouraged to explore new methodologies that balance performance, explainability, sustainability, and resilience. Attention should also be given to responsible data usage, privacy, fairness, and the societal consequences of intelligent technologies. Ultimately, trustworthy and explainable intelligence can strengthen confidence in AI-enabled systems and facilitate their adoption in real-world applications. This conference theme aims to bring together researchers and practitioners to advance intelligent systems that are not only smarter, but also more sustainable, resilient, transparent, and beneficial to society.
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AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
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CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312

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