Call For Papers
The ICFEED aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.
The conference highlights advancements in Data Science, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.
Authors are invited to submit papers addressing, but not limited to, the following areas:
- Feature engineering techniques for engineering datasets
- Importance of feature selection in data science
- Case studies of feature engineering in practice
- Automated feature extraction methods
- Challenges in high-dimensional feature spaces
- Feature engineering for time series data
- Applications of domain knowledge in feature design
- Feature engineering for machine learning models
- Visualization techniques for feature analysis
- Impact of feature engineering on model performance
- Future trends in feature engineering practices
- User experience design for feature engineering tools
- Ethical considerations in feature selection
- Collaborative feature engineering approaches
- Scalability issues in feature engineering
- Integrating feature engineering with data pipelines
- Data quality issues in feature engineering
- Frameworks for evaluating feature importance
- Real-time feature engineering for streaming data
- Interdisciplinary approaches to feature engineering
Assessment
Submissions will be assessed for originality, innovation, and relevance. Accepted papers will be presented at the conference and considered for publication opportunities in reputed academic platforms.
Registration
Participants are requested to complete the registration process following acceptance of their paper. Registration ensures inclusion in the conference schedule and official records.
Publication
All accepted manuscripts will be eligible for publication consideration in conference proceedings and associated academic journals.