Call For Papers - The World's Largest Index/List of Call For Papers

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

URL: https://nlp2026.org/dscc/index
Event Date: 2026-04-18 ~ 2026-04-19
Submission Date: 2026-04-11
Location: Melbourne, Australia

Data Mining & Analysis Health & Medical Sciences (General)

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

April 18 ~ 19, Melbourne, Australia

https://nlp2026.org/dscc/index

Scope & Topics

The 7^thInternational 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 the 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.