7th International Conference on Data Mining and Software Engineering (DMSE 2026)
July 16 ~ 17, 2026, London, United Kingdom Scope & Topics The 7th International Conference on Data Mining and Software Engineering (DMSE 2026) aims to provide a premier international forum for researchers, practitioners, and industry experts to share their knowledge, insights, and results in the theory, methodology, and applications of Data Mining and Software Engineering. As these fields continue to evolve rapidly, driven by advances in artificial intelligence, large-scale data analytics, and modern software development practices, DMSE 2026 seeks to foster deeper understanding, spark innovation, and promote meaningful collaboration across disciplines.
The goal of the conference is to bring together leading minds from academia and industry to explore emerging trends, address contemporary challenges, and establish new partnerships in Data Mining and Software Engineering. By bridging foundational research with real world applications, DMSE 2026 provides a platform for exchanging ideas that shape the future of intelligent systems, data driven engineering, and next generation software technologies.
Authors are invited to contribute high quality research papers, case studies, survey articles, and industrial experiences that demonstrate significant advances in the following areas, but are not limited to: Topics of interest include, but are not limited to, the following Foundations of Data Mining and Software Engineering
- Algorithms, Models, and Theory for Data Mining
- Foundations of Software Engineering
- Formal Methods, Verification, and Model Checking
- Programming Languages, Type Systems, and Semantics
- Neuro Symbolic AI and Logic Guided Learning
Machine Learning, AI and Knowledge Discovery
- Large Scale Machine Learning and Deep Learning
- Generative AI, LLMs, and Autonomous AI Agents
- Retrieval Augmented Generation (RAG) Systems and Evaluation
- Multimodal, Self-Supervised, and Transfer Learning
- Explainable, Trustworthy, and Responsible AI
- Knowledge Graphs, Knowledge Based Systems, and Reasoning
- Privacy Preserving ML (Federated Learning, Differential Privacy)
- Causal Machine Learning and Causal Discovery
AI for Software Engineering (AI4SE)
- AI Driven Code Generation, Completion, and Synthesis
- Automated Software Testing, Debugging, and Repair
- AI Assisted Refactoring, Optimization, and Maintenance
- Prompt Engineering and Prompt Based SE Workflows
- Benchmarking and Evaluation of AI Models for SE
- Autonomous SE Agents for Planning, Coding, Testing, and Deployment
- Human AI Collaboration in Software Development
Software Engineering for AI Systems (SE4AI)
- Engineering LLM Based Applications and AI Native Systems
- Guardrails, Hallucination Mitigation, and Safety Layers
- Data Centric AI and Data Quality Engineering
- MLOps, DataOps, and Continuous Delivery for ML Systems
- ML System Observability, Drift Detection, and AI Incident Response
- AI Governance, Risk, and Compliance Engineering
Data Driven Software Engineering
- Mining Software Repositories (MSR)
- Empirical Software Engineering and Evidence Based Methods
- Developer Productivity, Behavior, and Cognitive Analytics
- Socio Technical Systems and Collaboration Analytics
- Software Analytics and Data Driven Decision Making
- Technical Debt Detection, Prediction, and Management
- Continuous Experimentation, A/B Testing, and Causal Inference in SE
Software Architecture, Systems and Platforms
- Cloud Native Software Engineering and Distributed Systems
- Microservices, Serverless Computing, and Containerization
- Edge, IoT, and Embedded Software Systems
- Cyber Physical and Real Time Systems
- Observability, Telemetry, and Runtime Analytics
- Performance Engineering and Optimization
- Quantum Software Engineering and Quantum Programming Tools
Software Quality, Testing and Reliability
- Automated Test Generation, Fuzzing, and Mutation Testing
- Software Reliability, Resilience, and Dependability
- Software Maintenance, Evolution, and Reengineering
- Quality Assurance, Metrics, and Continuous Improvement
- Performance, Scalability, and Stress Testing
Security, Privacy and Trust
- Software Security and Vulnerability Detection
- Secure Software Supply Chains and DevSecOps
- Threat Modeling, Attack Simulation, and Security Testing
- Adversarial ML, Robustness, and AI Safety
- Trustworthy Software Systems and Compliance
Web, Search, Mobile and Emerging Platforms
- Web Scale Systems and Web Engineering
- Search Engines, Information Retrieval, and Recommendation Systems
- Mobile, Ubiquitous, and Context Aware Computing
- AR/VR, Immersive Systems, and Interactive Software
- Blockchain, Smart Contracts, and Decentralized Applications
Applications, Domains and Interdisciplinary Areas
- Data Mining Applications in Healthcare, Finance, Education, and Smart Cities
- Learning Analytics, Educational Data Mining, and AI in Education
- Sustainable and Green Software Engineering
- Multimedia Systems, Vision Driven Applications, and Multimodal Analytics
- Social Computing, Digital Ecosystems, and Human Centered AI
Paper Submission Authors are invited to submit papers through the conference Submission System by May 02, 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 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 DMSE 2026, after further revisions, will be published in the special issue of the following journals. Important Dates | Submission Deadline | : | May 02, 2026 | | Authors Notification | : | June 20, 2026 | | Final Manuscript Due | : | June 27, 2026 |
Co - Located Event ***** The invited talk proposals can be submitted to dmse@cmla2026.org
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