6th International Conference on Big Data, IoT and Machine Learning (BIOM 2026)
May 23 ~ 24, 2026, Vancouver, Canada Scope & Topics 6th International Conference on Big Data, IoT and Machine Learning (BIOM 2026) serves as a premier global forum for presenting innovative ideas, research developments and emerging trends in the rapidly evolving fields of Big Data, the Internet of Things (IoT) and Machine Learning. As data driven intelligence, connected systems and AI powered technologies continue to transform industries and society, BIOM 2026 aims to bring together researchers, practitioners and industry experts to exchange knowledge, discuss challenges and explore breakthroughs shaping the next generation of intelligent systems..
The conference encourages contributions that advance the state of the art in large scale data processing, distributed and federated learning, edge intelligence, 5G/6G enabled IoT, trustworthy and robust AI, digital twins, data centric AI and emerging technologies such as quantum machine learning and block chain based analytics. BIOM 2026 particularly welcomes work that bridges theory and practice, addresses real world deployment challenges and demonstrates the impact of Big Data, IoT and ML in complex, data intensive environments.
Authors are invited to submit original research articles, project reports, survey papersandindustrial case studies that illustrate significant advances in the field. Submissions may address any of the conference themes, including, but not limited to, the topics listed below. Topics of interest include, but are not limited to, the following Big Data Systems, Infrastructure and Platforms
- Distributed and Cloud Native Data Platforms
- Data Lakes, Lake houses and Modern Data Architectures
- Large Scale Data Processing Systems (Spark, Flink, Ray)
- High Performance and Parallel Computing for Big Data
- Edge to Cloud Data Pipelines and Streaming Architectures
Big Data Analytics, Mining and Applications
- Large Scale Data Mining and Knowledge Discovery
- Graph Mining, Network Science and Graph Based Analytics
- Spatiotemporal and Geospatial Data Analytics
- Realtime and Streaming Data Analytics
- Domain Driven Analytics (Healthcare, Finance, Climate, etc.)
Data Management, Governance and Quality
- Data Integration, Cleaning and Wrangling
- Data Governance, Lineage and Compliance
- Data Quality, Bias Detection and Fairness
- Metadata Management and Semantic Technologies
- Datacentric AI and Data Quality Engineering
Security, Privacy and Trust in DataDriven Systems
- Big Data Security, Privacy and Trust
- Differential Privacy and PrivacyPreserving Analytics
- Secure Multiparty Computation and Homomorphic Encryption
- Federated Security and Secure Data Sharing
- ZeroTrust Architectures for IoT and Edge Systems
Machine Learning and AI for Big Data
- Scalable Machine Learning Algorithms
- Distributed, Federated and Split Learning
- Deep Learning Architectures and Optimization
- Foundation Models and Large Scale Pretraining
- Multimodal Learning (VisionLanguageSensor Fusion)
- AutoML, Neural Architecture Search and Model Compression
- Causal Inference and Causal Machine Learning
Trustworthy, Robust and Safe Machine Learning
- Adversarial Machine Learning and Robustness
- Safe and Reliable ML Systems
- ML under Distribution Shift
- Explainable and Interpretable ML
- ML Risk Assessment and Governance
ML Systems, Deployment andMLOps
- Scalable Training and Inference Systems
- ML Model Deployment, Monitoring and Drift Detection
- ML Observability and Lifecycle Management
- Data/Model Versioning and Reproducibility
- RealTime ML and Online Learning
IoT Systems, Architectures and Connectivity
- IoT Architectures, Protocols and Standards
- Edge and Fog Computing for IoT
- 5G/6GEnabled IoT and UltraReliable LowLatency IoT
- IoT Interoperability and LargeScale IoT Platforms
- ResourceEfficient IoT Systems
IoT Applications, Sensing and CyberPhysical Systems
- Industrial IoT (IIoT) and Industry 4.0
- Environmental Monitoring and Precision Agriculture
- Wearables, Healthcare IoT and Remote Sensing
- Autonomous Systems and CyberPhysical Systems
- Sensor Fusion and Intelligent Sensing
Advanced IoT Security and Resilience
- Lightweight Cryptography for IoT
- Secure Firmware, OTA Updates and Device Hardening
- Intrusion Detection for IoT and Edge Systems
- Resilient IoT Architectures and Fault Tolerance
Edge Intelligence and Distributed AI
- Edge AI and OnDevice Machine Learning
- Collaborative and Federated Edge Intelligence
- ResourceEfficient ML for Edge and IoT Devices
- LowLatency AI and RealTime Inference
Networking for Big Data, IoTand ML
- 5G/6G Networks for DataIntensive Applications
- Network Slicing and QoS for IoT and ML Workloads
- SoftwareDefined Networking (SDN) and Network Virtualization
- DataDriven Network Optimization
Digital Twins and Emerging Technologies
- Digital Twins for IoT, Smart Infrastructure and CPS
- DataDriven Simulation and Predictive Modeling
- Blockchain for IoT, Data Integrity and Secure Analytics
- Quantum Machine Learning and Quantum Data Processing
- Generative AI for IoT and Big Data Applications
Federated Analytics and Collaborative Intelligence
- Federated Data Mining and Knowledge Discovery
- CrossDevice and CrossSilo Analytics
- PrivacyPreserving Collaborative Computation
Sustainable AI and Data Systems
- Green AI and EnergyEfficient ML
- CarbonAware Data Processing
- Sustainable IoT and Edge Systems
RealWorld Deployments, Benchmarks and Case Studies
- Experimental Results and Deployment Scenarios
- LargeScale System Benchmarking and Performance Evaluation
- Industrial Applications and Technology Transfer
Paper Submission Authors are invited to submit papers through the conference Submission System by February 21, 2026. 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 BIOM 2026, after further revisions, will be published in the special issue of the following journals. Important Dates | Submission Deadline | : | February 21, 2026 | | Authors Notification | : | March 28, 2026 | | Final Manuscript Due | : | April 04, 2026 |
Co - Located Event ***** The invited talk proposals can be submitted to biom@crbl2026.org |
