7th International Conference on Big Data and Applications (BDAP 2026)

Program Committee

Accepted Papers

Toronto, Canada

Scope Call for Participation

The 7^th 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.

Call for Papers

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.

Important Dates

Second Batch : Submissions after May 11, 2026

Submission Deadline

July 18, 2026(Final Call)

Authors Notification

July 23, 2026

Registration & camera - Ready Paper Due

July 24, 2026

Other Conferences

Past Events

Invited Talk

Proceedings

Hard copy of the proceedings will be distributed during the Conference. The softcopy will be available on AIRCC Digital Library

Welcome to BDAP 2026