BDAP 2026 (International Conference on Big Data and
Applications) is an academic conference held in Toronto, Ontario, Canada on 2026-07-25. The paper submission deadline is 2026-07-18 (extended). Acceptance notifications are sent on 2026-07-23.
7th International Conference on Big Data and Applications (BDAP 2026)
July 25 ~ 26, 2026, Toronto, Canada
https://ais2026.org/bdap/index
Scope
The 7th International Conference on Big Data and Applications (BDAP 2026) will serve as a premier global forum for presenting innovative ideas, advanced methodologies, cutting edge technologies, and impactful research in the rapidly evolving field of Big Data. As data continues to grow in scale, complexity, and strategic importance, BDAP 2026 aims to bring together researchers, practitioners, industry experts, and technology leaders to explore the latest breakthroughs and emerging trends shaping the future of data driven intelligence.
BDAP 2026 provides a dynamic platform for the exchange of knowledge and collaboration across academia and industry. The conference encourages discussions on the newest challenges, opportunities, and advancements in Big Data infrastructure, analytics, machine learning, data management, cloud native systems, and real world applications across diverse domains. By fostering interdisciplinary dialogue and showcasing high impact research, BDAP 2026 supports the development of next generation data technologies that drive innovation, efficiency, and societal progress.
Authors are solicited to submit works that illustrate research results, project outcomes, survey studies, and industrial experiences that describe meaningful progress in Big Data and its applications. Submissions may address topics listed in the BDAP 2026, including but not limited to:
Topics of interest include, but are not limited to, the following
Big Data Foundations, Infrastructure and Platforms
• Distributed Big Data Systems and Architectures
• Cloud Native Data Platforms (Kubernetes, Serverless, Lakehouses)
• Data Mesh, Data Fabric and Modern Data Stacks
• High Performance Computing (HPC) for Big Data
• Edge Cloud Continuum, Fog Computing and IoT Driven Big Data
• 5G/6G Networks for Big Data and Ultra Low Latency Analytics
• Streaming Data Platforms (Kafka, Flink, Spark Structured Streaming)
• Data Contracts, Schema Evolution and Contract Driven Pipelines
Big Data Management, Governance and Quality
• Data Integration, Cleaning and Wrangling at Scale
• Metadata Management, Data Catalogs and Lineage Tracking
• Data Versioning, Provenance and Reproducibility
• Data Quality, Reliability Scoring and Trustworthy Pipelines
• Privacy Preserving Data Management (DP, MPC, Homomorphic Encryption)
• Data Observability, Monitoring, Drift Detection and Root Cause Analysis
• Compliance Aware Data Systems and AI Governance
Big Data Analytics, Mining and Knowledge Discovery
• Large Scale Data Mining and Pattern Discovery
• Graph Mining, Network Analysis and Knowledge Graphs
• Spatio Temporal Data Mining and Geo Analytics
• Social Media Analytics and Behavioral Modeling
• Text, Web and Multimedia Big Data Analytics
• Real Time Analytics, Complex Event Processing and Online Learning
• High Dimensional Data Analysis and Feature Engineering at Scale
• Knowledge Augmented Data Processing and Semantic Integration
Machine Learning, AI and Big Data Intelligence
• Machine Learning and Deep Learning for Big Data
• Foundation Models and Large Scale Pretraining on Big Data
• Distributed ML, Federated Learning and Collaborative Analytics
• Reinforcement Learning for Big Data Systems
• Causal ML, Explainable AI (XAI) and Trustworthy Big Data AI
• AutoML, Hyperparameter Optimization and Scalable ML Pipelines
• Data Centric AI and Data Driven Model Optimization
• Data Efficient AI: Pruning, Deduplication and Curriculum Data Pipelines
• Big Data Pipelines for LLM Training and Evaluation
Big Data Security, Privacy and Trust
• Big Data Security Architectures and Threat Detection
• Privacy Preserving Analytics (DP, MPC, Homomorphic Encryption)
• Secure Data Sharing, Access Control and Identity Management
• Blockchain for Big Data Integrity, Provenance and Auditability
• Trustworthy AI, Bias Mitigation and Ethical Big Data Systems
• Secure Data Clean Rooms and Cross Organizational Federated Analytics
Big Data Search, Indexing and Query Processing
• Large Scale Search Systems and Information Retrieval
• Distributed Query Processing and Optimization
• Indexing for High Dimensional, Graph and Multimodal Data
• Semantic Search, Hybrid Search and Knowledge Augmented Retrieval
• Vector Databases, Embedding Based Retrieval and ANN Search
• GPU Accelerated Vector Search and Hybrid Sparse Dense Indexing
• Learned Index Structures for Big Data
Cloud, HPC and Advanced Computing for Big Data
• Cloud Computing Architectures for Big Data
• GPU/TPU Acceleration for Big Data Workloads
• Serverless Computing and Elastic Data Processing
• Energy Efficient Big Data Computing and Green Data Systems
• Quantum Computing for Big Data Analytics
• Simulation Driven Data Processing and Synthetic Environments
Big Data Applications across Domains
• Healthcare, Bioinformatics, Genomics and Precision Medicine
• Smart Cities, IoT, Mobility and Urban Analytics
• Finance, Economics, Fraud Detection and Risk Modeling
• Education, Learning Analytics and EdTech
• Climate Science, Sustainability and Environmental Monitoring
• Cybersecurity, Threat Intelligence and Digital Forensics
• Retail, E commerce, Personalization and Recommendation Systems
• Big Data for Robotics, Autonomous Vehicles and Sensor Fusion
• Digital Twins and Real Time Simulation Ecosystems
Emerging Trends in Big Data and Future Directions
• Multimodal Big Data (Text, Image, Video, Audio, Sensor Data)
• Cross Modal Fusion and Multimodal Embeddings at Scale
• Synthetic Data Generation and Simulation Driven Analytics
• Data Lakehouse Evolution (Delta Lake, Iceberg, Hudi)
• Real Time AI, Streaming ML and Event Driven Intelligence
• Big Data for LLMs: Dataset Curation, Filtering and Scaling
• Digital Twins, Simulation Platforms and Virtual Environments
• Quantum Accelerated Data Processing
• ESG, Sustainability and Carbon Aware Data Systems
• Retrieval Augmented Data Systems (RAG Optimized Pipelines)
• Autonomous Data Agents and AI Driven ETL/ELT
Paper Submission
Authors are invited to submit papers through the conference Submission System by July 18, 2026 (Final Call). Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).
Selected papers from BDAP 2026, after further revisions, will be published in the special issue of the following journal.
• International Journal of Data Mining & Knowledge Management Process (IJDKP)
• International Journal of Database Management Systems (IJDMS)
• International Journal on Web Service Computing (IJWSC)
• Information Technology in Industry (ITII)
Important Dates
• Submission Deadline: July 18, 2026 (Final Call)
• Authors Notification: July 23, 2026
• Registration & camera - Ready Paper Due: July 24, 2026
Contact Us
Here's where you can reach us : [email protected] (or) [email protected]
Submission URL: https://csit2026.org/submission/index.php
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