Call For Papers
The ICNDSA-2026 conference aims to serve as a global platform for professionals, researchers, educators, entrepreneurs, and enthusiasts to exchange and share their insights, challenges, research results, innovative solutions, and applications across the diverse spectrum of Data Science and Analytics.
With a focus on advancing the frontiers of knowledge and fostering interdisciplinary collaboration, ICNDSA-2026 welcomes contributions that highlight the latest developments, methodologies, and real-world implementations of emerging computing paradigms.
We invite researchers, practitioners, and academics to submit original research papers, case studies, and technical reports in the broad areas of Data Science and Analytics, including (but not limited to):
Track 1: Advanced AI and Machine Learning
- Deep Learning Innovations
- Reinforcement Learning Applications
- Explainable AI Applications
- AutoML Frameworks and Libraries
- Hyperparameter Optimization
- Quantum Computing in Data Science
Track 2: Big Data, IoT, and Real-Time Analytics
- Distributed Computing and Storage Solutions
- Real-time Data Processing
- Big Data Integration and Management
- Smart City Data Applications
- Real-time Sensor Data Processing
- Predictive Maintenance with IoT Data
- Edge Computing for Data Processing
Track 3: Data Science in Healthcare, Finance, and Business
- Precision Medicine and Genomics
- Health Informatics Systems
- Data-Driven Public Health
- Algorithmic Trading and Market Analysis
- Risk Management and Fraud Detection
- Blockchain and Cryptocurrency Analytics
- Predictive Analytics in Business
- Data-Driven Marketing Strategies
- Customer Insights and Personalization
Track 4: Data Science for Environmental and Social Impact
- Climate Data Analysis and Modeling
- Social Network Analysis
- Sustainable Development Analytics
Track 5: Tools, Platforms, and Emerging Innovations
- Open Source Tools and Libraries
- Enterprise Data Science Platforms
- Comparative Studies of Data Science Software
- Innovations in Data Engineering
