On-location / Digital Conference

International Conference on Feature Engineering in Engineering Datasets (ICFEED-26)

30th - 31st Oct 2026,Athens, Greece

In Association With:

Call for Paper


Important Dates


Early Bird Registration

30th Sep 2026

Paper Submission Deadline

5th October 2026

Registration Deadline

15th October 2026

Conference Date

30th - 31st Oct 2026

Conference Updates:

"Stay updated with Science Cite Conference news."

  • Early-Bird Registration Reminder:
    Early-bird registration for the Science Cite Conference in Athens ends soon! Register Now!
  • Certificate of Presentation – Recognizing Your Contribution:
    Receive a Certificate of Presentation to recognize your participation in Athens conference.
  • Peer Review Process:
    The peer review process will begin soon for Athens conference.
  • Networking with Global Experts:
    Join global experts at our conference in Athens.
  • Opportunity for Scopus-Indexed Journal Publication:
    Your research could be published in a Scopus-Indexed Journal. Submit Your Abstract
  • SDG-Inspired Conference Focus:
    Present your work aligned with Sustainable Development Goals.

Call For Papers

The ICFEED bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Feature Engineering in Engineering Datasets, encouraging applied research, case studies, and industry-driven innovations.

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 evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in relevant journals and proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.

Indexed / Supported By

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Academic Institutions Whose Scholars Have Contributed

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