7th International Conference on Data Science and Cloud Computing (DSCC 2026)

7th International Conference on Data Science and Cloud Computing (DSCC 2026)

April 18 ~ 19, Melbourne, Australia

https://nlp2026.org/dscc/index

Scope & Topics

The 7th International Conference on Data Science and Cloud Computing (DSCC 2026) brings together the global research community at a moment when data, intelligence, and scalable computing are reshaping every scientific and industrial frontier. As AI systems grow more capable, data ecosystems expand in complexity, and cloud infrastructures evolve into intelligent, autonomous platforms, the need for a unified forum that bridges these domains has never been greater.

DSCC 2026 serves as that meeting point, a space where breakthroughs in machine learning, data science, cloud architectures, and emerging computational technologies converge. The conference highlights both the theoretical foundations and the real world systems that power modern AI, from foundation models and multimodal learning to distributed training, edge intelligence, and quantum enhanced computation. It embraces the full spectrum of innovation: rigorous algorithms, scalable systems, responsible technology, and high impact applications across science, society, and industry.

Join us as we explore the technologies defining the future of computation and the ideas that will define the decade ahead.

Topics of interest include, but are not limited to, the following

Track 1: Artificial Intelligence & Machine Learning

• Foundation Models, LLMs, and Multimodal AI
• Generative AI and Synthetic Data
• Optimization for ML and Large Scale Training
• Continual, Transfer, Meta Learning, and Lifelong Learning
• Reinforcement Learning and Decision Making
• Graph Machine Learning and Network Science
• Theoretical ML and Generalization
• Robustness, Adversarial ML, and OOD Generalization
• Explainable, Interpretable, and Trustworthy AI
• Neuroscience Inspired AI and Cognitive Modeling
• Human AI Collaboration and Interactive ML

Track 2: Data Science, Analytics & Applications

• Big Data Analytics and Knowledge Discovery
• Time Series, Forecasting, and Anomaly Detection
• Statistical Learning, Bayesian Methods, and Probabilistic Modeling
• Data Visualization, Immersive Analytics, and HCI
• Streaming Analytics and Real Time Data Processing
• Data Quality, Cleaning, Provenance, and Reproducibility
• Domain Applications:
• Healthcare, Precision Medicine, Bioinformatics
• Finance, Economics, and Risk Modeling
• Social Media, Behavioral Analytics, Digital Society
• Sustainability, Climate Science, Environmental Data
• Education and Learning Analytics
• Geospatial AI and Earth Observation
• Computational Social Science

Track 3: Computer Vision, Multimodal & Embodied AI

• 2D/3D Vision, Scene Understanding, Video Analytics
• Vision Language Models and Multimodal Fusion
• Embodied AI, Robotics Perception, and VLA Models
• Spatial Computing, AR/VR/MR Analytics
• Digital Twins and Simulation Driven Perception

Track 4: Cloud Computing & Distributed Systems

• Cloud Native AI/ML Systems
• Distributed Training and Inference at Scale
• Serverless Computing, FaaS, and Event Driven Systems
• Cloud Edge Device Collaboration and Edge AI
• High Performance Computing (HPC) for AI and Data Science
• Cloud Storage, Data Lakes, Lakehouse, and Vector Databases
• Cloud Observability, Reliability Engineering, and SRE
• Networking for AI Workloads and High Performance Interconnects
• Cost Optimization, FinOps, and Green Cloud Computing
• Cloud based Data Science Platforms and MLOps

Track 5: Security, Privacy & Responsible Technology

• Privacy Preserving ML (FL, DP, MPC)
• AI Security, Model Integrity, and Watermarking
• Secure Data Pipelines, Governance, and Compliance
• Ethical AI, Fairness, Accountability, Transparency
• AI Governance, Policy, and Regulation
• Zero Trust Architectures and Confidential Computing

Track 6: Emerging Technologies & Interdisciplinary Research

• IoT, Cyber Physical Systems, and Sensor Analytics
• Edge Computing, TinyML, and On Device Intelligence
• Quantum Computing and Quantum Machine Learning
• AI for Scientific Discovery (AI4Science)
• Autonomous Systems, Robotics, and Intelligent Control
• AI Driven Software Engineering and Code Intelligence
• Simulation Driven Science and Digital Twins


Paper Submission

Authors are invited to submit papers through the conference Submission System by April 11, 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 (H index 45) in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from DSCC 2026, after further revisions, will be published in the special issue of the following journals.

• The International Journal of Database Management Systems (IJDMS)
• International Journal of Data Mining & Knowledge Management Process (IJDKP) 
• International Journal on Cloud Computing: Services and Architecture (IJCCSA)
• Information Technology in Industry (ITII)

Important Dates
(last call: submissions after March 23)
• Submission Deadline: April 11, 2026(Final Call)
• Authors Notification: April 16, 2026
• Registration & Camera-Ready Paper Due: April 17, 2026

Contact Us:

Here's where you can reach us: [email protected] (or) [email protected]

Submission Link: https://cse2026.org/submission/index.php