

# Event Details

- **Event Name**: 7th International Conference on Big Data and Machine Learning (BDML 2026)
- **Event Start and End Date**: Sat, 27 Jun, 2026 at 10:00 am – Sun, 28 Jun, 2026 at 10:00 am (+02:00)
- **Event Description**: 7th International Conference on Big Data and Machine Learning (BDML 2026)June 27 ~ 28, 2026, Copenhagen, Denmarkhttps://bdml2026.org/indexScopeThe 7th International Conference on Big Data and Machine Learning (BDML 2026) brings together researchers, practitioners and industry leaders to explore the rapidly evolving landscape of data driven intelligence. As Big Data and Machine Learning continue to transform science, engineering, business and society, BDML 2026 serves as a premier venue for presenting innovative ideas, breakthrough methodologies and innovative applications that push the boundaries of what intelligent systems can achieve. The conference provides a dynamic environment for discussing emerging challenges, sharing novel solutions and shaping the future directions of the field.BDML 2026 welcomes high quality contributions that display original research results, visionary projects, comprehensive surveys and real world industrial experiences. Submissions are encouraged from all areas of Big Data and Machine Learning, particularly those that demonstrate significant advances in theory, systems, algorithms and applications.Topics of interest include, but are not limited to, the followingFoundation Models, Generative AI and Multimodal SystemsLarge Language Models (LLMs): architectures, scaling laws, training, alignmentMultimodal foundation models (vision language, audio text, video language)Retrieval Augmented Generation (RAG) and knowledge grounded AIEfficient fine tuning, distillation, quantization and model compressionDiffusion models and generative modeling for images, audio, video and 3DSafety, robustness and evaluation of foundation modelsMachine Learning Theory, Algorithms and OptimizationOptimization methods for deep and large scale modelsRepresentation learning and self supervised learningProbabilistic modeling, Bayesian methods and uncertainty quantificationMeta learning, few shot learning and transfer learningOnline, continual and lifelong learningCausal inference, causal discovery and counterfactual reasoningML Systems, Infrastructure and Scalable ComputingDistributed training systems, parallelization strategies and schedulingML compilers, accelerators and hardware -software co designCloud native, edge and serverless ML systemsHigh performance computing for ML and data intensive workloadsInference optimization, serving systems and low latency ML pipelinesEnergy efficient ML, Green AI and sustainable computingBig Data Systems, Management and EngineeringScalable data processing architectures and dataflow systemsData engineering, pipelines, orchestration and workflow automationData integration, cleaning, quality and governanceReal time and streaming data analyticsData compression, indexing and query optimizationPrivacy preserving data management (DP, MPC, HE)Data Mining, Knowledge Discovery and Graph IntelligenceLarge scale data mining algorithms and theoryGraph neural networks (GNNs) and graph representation learningKnowledge graphs, reasoning and graph miningTemporal, spatial and spatiotemporal data miningAnomaly detection, fraud detection and rare event modelingRecommender systems and personalizationResponsible, Trustworthy and Secure AIExplainability, interpretability and transparency in MLFairness, bias mitigation and ethical AIAI governance, policy and regulatory complianceAdversarial ML, robustness and secure model trainingPrivacy preserving ML (federated learning, DP, secure aggregation)ML for cybersecurity and threat intelligenceDistributed, Federated and Edge IntelligenceFederated learning algorithms, systems and applicationsCollaborative and decentralized MLEdge AI, on device learning and TinyML6G, IoT and cyber physical systems for ML and data analyticsResource constrained learning and communication efficient MLAutonomous Agents, RL and Decision MakingReinforcement learning theory and applicationsMulti agent systems and coordinationLLM based agents and tool using AI systemsPlanning, control and sequential decision makingSimulation based learning and digital twinsScientific ML, Simulation and Domain ApplicationsML for physics, chemistry, biology and materials scienceClimate modeling, environmental analytics and sustainabilityHealthcare analytics, medical AI and computational biologyFinance, economics and risk modelingSmart cities, transportation and mobility analyticsMultimedia, vision, speech and natural language analyticsEvaluation, Benchmarking and Data Centric AIDataset creation, curation and governanceData centric AI methodologies and toolingBenchmarking ML systems and reproducibility studiesRobust evaluation protocols for large scale modelsSynthetic data generation and simulation driven datasetsPaper SubmissionAuthors are invited to submit papers through the conference Submission System by March 29, 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 &amp; Information Technology (CS &amp; IT) series (Confirmed).Selected papers from BDML 2026, after further revisions, will be published in the special issue of the following journal.Information Technology in Industry (ITII)International Journal of Data Mining &amp; Knowledge Management Process (IJDKP)International Journal of Database Management Systems (IJDMS)Machine Learning and Applications: An International Journal (MLAIJ)Advances in Vision Computing: An International Journal (AVC)International Journal of Grid Computing &amp; Applications (IJGCA)Important Dates(2nd batch : submissions after March 23)Submission Deadline: March 29, 2026Authors Notification: May 23, 2026Registration &amp; Camera-Ready Paper Due: May 30, 2026Contact UsHere’s where you can reach us :bdml@bdml2026.org (or) bdmlconf@yahoo.com
- **Event URL**: https://allevents.in/copenhagen/7th-international-conference-on-big-data-and-machine-learning-bdml-2026/80001557863675
- **Event Categories**: concerts, business, conferences, it, art, literary-art
- **Interested Audience**: 
  - total_interested_count: 0

## Ticket Details

- **Ticket URL**: https://bdml2026.org/index

## Event venue details

- **city**: Copenhagen 
- **state**: SK
- **country**: Denmark
- **location**: Copenhagen
- **lat**: 55.6760968
- **long**: 12.5683371
- **full address**: Copenhagen, Copenhagen, Denmark, Copenhagen 

## Event Organizer details

- **affiliate_id**: 8
- **organizer**: DMSE 2026 (https://allevents.in/org/dmse-2026/27513206)

## Event gallery

- **Alt text**: banner
  - **Image URL**: https://cdn2.allevents.in/thumbs/thumb69a532fca427c.jpg
- **Alt text**: thumbnail
  - **Image URL**: https://dyn-image.allevents.in/generate-image?v=4&title=7th+International+Conference+on+Big+Data+and+Machine+Learning+%28BDML+2026%29&date=27+Jun

## FAQs

- **Q**: When is the event happening?
  - **A:** Sat, 27 Jun, 2026 at 10:00 am (+02:00)
- **Q**: Where is the event happening?
  - **A:** Copenhagen, Copenhagen, Denmark, Copenhagen
- **Q**: Who is organizing the event?
  - **A:** DMSE 2026
- **Q**: What type of event is this?
  - **A:** concerts, business, conferences, it, art, literary-art
- **Q**: Where can I find ticket details about 7th International Conference on Big Data and Machine Learning (BDML 2026) ?
  - **A:** You can find ticket details about this event on AllEvents.

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