Conference Information

BDCC 2026: EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing

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Submission Date:
2026-09-30 Due in 3 days
Notification Date:
2026-10-20
Conference Date:
2026-12-03
Location:
Coimbatore, India
Years:
Viewed: 16506   Tracked: 2   Attend: 0

Conference Partner Index (CP-I)

50.4 / 100
Ranked #1,510 of 5,687 conferences · Top 27%

#25 of 298 in Energy & Environment #80 of 337 in Data Mining & Databases #145 of 741 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%)
62
Community attention (10%)
23
Public record completeness (15%)
55

Inputs used: Editions on record: 9 · Researchers following it here: 2 · 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 2026-09-26

Call For Papers

BDCC 2026 (EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing) is an academic conference held in Coimbatore, India on 2026-12-03. The paper submission deadline is 2026-09-30. Acceptance notifications are sent on 2026-10-20.

Scope The 9th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2026) continues the mission of advancing intelligent, scalable, and sustainable data-driven technologies for the next era of cognitive computing. Building upon previous editions, BDCC 2026 emphasizes trustworthy AI, ultra-efficient big data systems, and human-aligned cognitive intelligence to address global sustainability challenges. The conference explores next-generation big data analytics, adaptive cognitive architectures, and sustainable AI ecosystems, focusing on their transformative impact across smart societies, industry, healthcare, climate systems, and emerging digital infrastructures. Special attention is given to resilient, low-energy, and ethical AI solutions capable of operating on a scale in complex, real-world environments. BDCC 2026 serves as a premier interdisciplinary forum bringing together researchers, engineers, industry leaders, and policymakers to exchange ideas, present original research, and discuss future directions for responsible digital transformation. Contributions spanning theoretical foundations, applied innovations, experimental systems, and real-world deployments are strongly encouraged. Topics Quantum-inspired and hybrid quantum algorithms Neuromorphic and brain-inspired computing for energy-efficient big data processing Federated, decentralized, and self-learning cognitive systems Explainable, trustworthy, and ethical AI for big data decision-making Green AI models for reducing energy consumption and carbon emissions Energy-aware big data architectures and low-power AI accelerators Next-generation big data compression and adaptive model optimization Cognitive digital twins for smart cities, smart grids, and industrial sustainability Edge-AI and real-time analytics for traffic optimization and pollution reduction AI-driven predictive maintenance and resource optimization AI-powered early warning systems for climate and disaster resilience Big data analytics for environmental monitoring and climate modeling Sustainable water, energy, and waste management using cognitive intelligence Green blockchain technologies for secure and sustainable big data processing Human-centric AI for transparent and inclusive decision-making AI-driven drug discovery and personalized healthcare systems Cognitive IoT for smart healthcare and remote monitoring AI-powered big data analytics for space exploration and planetary sustainability Future Advancements
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