CfP/Topics – ICDATA'25

CALL FOR PAPERS – LIST OF TOPICS

ICDATA’25

The 21th International Conference on Data Science 2025

Date and Location: July 21 – 24, 2025, Las Vegas, USA
Luxor (MGM property)

Invitation: You are invited to submit a paper for consideration. The Congress is composed of a number of tracks (joint-conferences, tutorials, sessions, workshops, poster and panel discussions); all will be held simultaneously, same location and dates: July 21-24, 2025. The complete list of CSCE joint conferences can be found here. ICDATA is part of the Congress.

This year’s Congress will be held in person (face-to-face); however, online presentation options will also be available for authors and speakers who are unable to attend physically. We expect that the vast majority of speakers will attend in person, with most presentations being delivered face-to-face.

Publication: All accepted papers will be published by Springer Nature in the proceedings (Research Books) and indexed in major Science Citation Indexation databases.

It is also planned to publish a collection of selected extended papers in a book by De Gruyter.

Indexation: Scopus; DBLP, EI Engineering Index (Compendex, Inspec databases); Springer Link; Google Scholar; Conference Proceedings Citation Index (CPCI), part of Clarivate Analytics‘ Web of Science; ACM Digital Library; IO-Port; MathSciNet; Zentralblatt MATH, and others. Only about 5% of all journals and conference proceedings reach the same high level of scientific indexing as CSCE publications.

Sponsor: American Council on Science and Education, in collaboration with multiple institutions, Corporations, and funding agencies.

Scope: Submitted papers should be related to Data Science, Data Mining, Machine Learning, AI for Data Analytics, and similar topics.

Topics of interest include, but are not limited to, the following:

Data Mining/Machine Learning Tasks

Regression/Classification
Time series forecasting
Segmentation/Clustering/Association
Deviation and outlier detection</>
Explorative and visual data mining
Web mining
Mining text and semi-structured data
Temporal and spatial data mining
Multimedia mining (audio/video)
Mining „Big Data“
Others

Data Mining Algorithms

Artificial neural networks / Deep Learning / Large Language Models
Fuzzy logic and rough sets
Decision trees/rule learners
Support vector machines
Evolutionary computation/meta heuristics
Statistical methods
Collaborative filtering
Case based reasoning
Link and sequence analysis
Ensembles/committee approaches
Others

Data Mining Integration

Mining large scale data/big data
Data and knowledge representation
Data warehousing and OLAP integration
Integration of prior domain knowledge
Metadata and ontologies
Agent technolog ies for data mining
Legal and social aspects of data mining
Others

Data Mining Process

Data cleaning and preparation
Feature selection and transformation
Attribute discretisation and encoding
Sampling and rebalancing
Missing value imputation
Model selection/assessment and comparison
Induction principles
Model interpretation
Others

Data Mining Applications

Bioinformatics
Medicine Data Mining
Business / Corporate / Industrial Data Mining
Credit Scoring
Direct Marketing
Database Marketing
Engineering Mining
Military Data Mining
Security Data Mining
Social Science Mining
Data Mining in Logistics
Others

We particularly encourage submissions of industrial applications and case studies from practitioners. These will not be evaluated using solely theoretical research criteria, but will take general interest and presentation into consideration.

Data Mining Software

All aspects, modules, frameworks

Alternative and additional examples of possible topics include:

Data Mining for Business Intelligence
Emerging technologies in data mining
Computational performance issues in data mining
Data mining in usability
Advanced prediction modelling using data mining
Data mining and national security
Data mining tools
Data analysis
Data preparation techniques (selection, transformation, and preprocessing)
Information extraction methodologies >
Clustering algorithms used in data mining
Genetic algorithms and categorization techniques used in data mining
Data and information integration
Microarray design and analysis
Privacy-preserving data mining
Active data mining
Statistical methods used in data mining
Multidimensional data
Case studies and prototypes
Automatic data cleaning
Data visualization
Theory and practice – knowledge representation and discovery
Knowledge Discovery in Databases (KDD)
Uncertainty management
Data reduction methods
Data engineering
Content mining
Indexing schemes
Information retrieval
Metadata use and management
Multidimensional query languages and query optimization
Multimedia information systems
Search engine query processing
Pattern mining
Applications (examples: data mining in education, marketing, finance and financial services, business applications, medicine, bioinformatics, biological sciences, science and technology, industry and government, …)

Algorithms for Big Data

Data and Information Fusion
Algorithms (including Scalable methods)
Natural Language Processing
Signal Processing
Simulation and Modeling
Data-Intensive Computing
Parallel Algorithms
Testing Methods
Multidimensional Big Data
Multilinear Subspace Learning
Sampling Methodologies
Streaming
Others

Big Data Fundamentals

Novel Computational Methodologies
Algorithms for Enhancing Data Quality
Models and Frameworks for Big Data
Graph Algorithms and Big Data
Computational Science
Computational Intelligence
Others

Infrastructures for Big Data

Cloud Based Infrastructures (applications, storage & computing resources)
Grid and Stream Computing for Big Data
High Performance Computing, Including Parallel & Distributed Processing
Autonomic Computing
Cyber-infrastructures and System Architectures
Programming Models and Environments to Support Big Data
Software and Tools for Big Data
Big Data Open Platforms
Emerging Architectural Frameworks for Big Data
Paradigms and Models for Big Data beyond Hadoop/MapReduce, …
Others

Big Data Management and Frameworks

Database and Web Applications
Federated Database Systems
Distributed Database Systems
Distributed File Systems
Distributed Storage Systems
Knowledge Management and Engineering
Massively Parallel Processing (MPP) Databases
Novel Data Models
Data Preservation and Provenance
Data Protection Methods
Data Integrity and Privacy Standards and Policies
Data Science
Novel Data Management Methods
Crowdsourcing
Stream Data Management
Scientific Data Management
Others

Big Data Search

Multimedia and Big Data
Social Networks
Data Science
Web Search and Information Extraction
Scalable Search Architectures
Cleaning Big Data (noise reduction), Acquisition & Integration
Visualization Methods for Search
Time Series Analysis
Recommendation Systems
Graph Based Search and Similar Technologies
Others

Privacy in the Era of Big Data

Cryptography
Threat Detection Using Big Data Analytics
Privacy Threats of Big Data
Privacy Preserving Big Data Collection
Intrusion Detection
Socio-economical Aspect of Big Data in the Context of Privacy and Security
Others

Applications of Big Data

Big Data as a Service
Big Data Analytics in e-Government and Society
Applications in Science, Engineering, Healthcare, Visualization, Business, Education, Security, Humanities, Bioinformatics, Health Informatics, Medicine, Finance, Law, Transportation, Retailing, Telecommunication, all Search-based applications, …
Others

For Special Sessions, please have a look here.

Keynote Lectures and Tutorials: There will be between 10 and 15 Keynote lectures and Invited Talks; speakers include world-renowned scientists and educators. The names of Featured Keynote Speakers in recent years can be found here.

computing. We anticipate to have attendees from about 70 countries and territories. To get a feeling about the conferences‘ atmosphere, see some delegates photos available at (over 2,000 photos) here.