Conference Information

BDCloud 2026: International Conference on Big Data and Cloud Computing

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Submission Date:
2026-10-15 Closed
Notification Date:
2026-11-10
Conference Date:
2026-12-27
Location:
Kuala Lumpur, Malaysia
Years:
Viewed: 33710   Tracked: 10   Attend: 2
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BDCloud
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Conference Partner Index (CP-I)

54.7 / 100
Ranked #919 of 5,759 conferences · Top 16%

#42 of 339 in Data Mining & Databases #120 of 341 in Systems & Architecture

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%)
76
Community attention (10%)
37
Public record completeness (15%)
55

Inputs used: Editions on record: 16 · Researchers following it here: 10 · Researchers who opened this page in the past 24 months: 5

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 1.2 · Computed 2026-10-25

Call For Papers

BDCloud 2026 (International Conference on Big Data and Cloud Computing) is an academic conference held in Kuala Lumpur, Malaysia on 2026-12-27. The paper submission deadline is 2026-10-15. Acceptance notifications are sent on 2026-11-10.

Big data refers to datasets that exceed the processing capabilities of traditional software tools, characterized by diverse sources (Variety), large scale (Volume), and high-speed generation (Velocity). Ensuring its value (Value) and reliability (Veracity) is essential for effective decision-making. Meanwhile, cloud computing has emerged as a key platform for delivering IT resources and infrastructure as services, enabling cost-effective, on-demand access through pay-as-you-go models, reducing the need for significant capital investment. Topics of BDCloud 2026 include but are not limited to the following areas: Track 1: Cloud Computing Theory & Application – Fundamentals of cloud computing – Provisioning/pricing cloud models – Data storage in cloud computing – Resource scheduling in cloud computing – Fault tolerance and reliability in cloud computing – Access control to cloud computing – Monitoring and auditing in cloud Track 2: Cloud & Artificial Intelligence – AI-driven cloud services & operations – Use of cloud to improve AI deployment – Predictive analysis and federated learning – Automation for remediation & mitigation – Observability and transparency – Edge AI systems and applications – Cloud infrastructure for LLM Track 3: Data Privacy, Security, and Compliance – Encryption algorithms and secure communication – Homomorphic encryption – Data anonymization and de-identification – Access control and identity authentication – Defense mechanisms in cloud system – Security auditing and risk assessment – Privacy-preserving machine learning and AI models Track 4: Big Data Mining & Analytics – Big data visualization – Big data mining and analytics on cloud – Scalability of machine learning models – Distributed and federated datasets – Big data scheduling and optimization – Real-time data stream analysis – Big data applications
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