Conference Information

MLIoT 2026: International Conference on Machine Learning and IoT

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MLIoT
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Submission Date:
2026-09-08
Notification Date:
2026-11-07
Conference Date:
2026-12-29
Location:
Online
Years:
Viewed: 9577   Tracked: 0   Attend: 1

Conference Partner Index (CP-I)

45.6 / 100
Ranked #2,676 of 5,682 conferences · Top 48%

#283 of 739 in Artificial Intelligence & Machine Learning #409 of 864 in Networks & Communications

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%)
43
Community attention (10%)
12
Public record completeness (15%)
55

Inputs used: Editions on record: 4 · Researchers who opened this page in the past 24 months: 4

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 2026-09-15

Call For Papers

MLIoT 2026 (International Conference on Machine Learning and IoT) is an academic conference held in Online on 2026-12-29. The paper submission deadline is 2026-09-08. Acceptance notifications are sent on 2026-11-07.

SCOPE 4th International Conference on Machine Learning and IoT (MLIoT 2026) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Machine Learning and Internet of Things (IoT). Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to: Topics of interest Artificial Intelligence Bayesian Network Computer Vision Connectivity and Networking Data Mining and Machine Learning Tools Deep Learning Electronics and Signal processing for IoT Experimental Results and Deployment Scenarios Intelligent System Architecture IoT IoT & Artificial Intelligence IoT Applications and Services IoT Big Data IoT-enabled Innovation and Entrepreneurship Learning in Knowledge-intensive Systems Learning Methods and Analysis Learning Problems Machine Learning and Analytics Machine learning & IoT Machine Learning Algorithms Neural Networks Predictive Learning Recent Trends and Developments of AI & IoT Reinforcement Learning Robotics, loT and Embedded System Security and Privacy for IoT Supervised Machine Learning Unsupervised Machine Learning
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