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

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Link: https://nlp2026.org/dscc/index
 
When Apr 18, 2026 - Apr 19, 2026
Where Melbourne, Australia
Submission Deadline Mar 14, 2026
Notification Due Apr 4, 2026
Final Version Due Apr 11, 2026
Categories    data science   cloud computing   artificial intelligence   computer science
 

Call For Papers

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

April 18 ~ 19, 2026, Melbourne, Australia

Hybrid -- Registered authors can present their work online or face to face.

Scope & Topics

7th International Conference on Data Science and Cloud Computing (DSCC 2026) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Data Science, Cloud Computing and Applications. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Data Science, Cloud Computing & Applications.

Authors are solicited to contribute to this conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Artificial Intelligence & applications.

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 March 14, 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 (H index 46) 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.

Important Dates

Submission Deadline: March 14, 2026
Authors Notification: April 04, 2026
Final Manuscript Due: April 11, 2026

Co - Located Event

***** The invited talk proposals can be submitted to dscc@nlp2026.org

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