7th International Conference on Data Science and Machine Learning (DSML 2026)

Schedule

Sat, 22 Aug, 2026 at 09:00 pm to Sun, 23 Aug, 2026 at 05:00 pm

UTC+01:00

Location

Dubai | Dubai, DU

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7th International Conference on Data Science and Machine Learning (DSML 2026)

 

August 22 ~ 23, 2026, Dubai, UAE

 

https://bibc2026.org/dsml/index

 

Hybrid -- Registered authors can present their work

Scope & Topics

 

7th International Conference on Data Science and Machine Learning (DSML 2026) ) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Data Science and Machine Learning. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Data Science and Machine Learning.

 

Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

 

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

 

Data Mining

 

·        Parallel and Distributed Data Mining Algorithms

·        Data Streams Mining, Graph Mining, Spatial Data Mining

·        Text video, Multimedia Data Mining, Web Mining

·        Pre-Processing Techniques, Visualization

·        Security and Information Hiding in Data Mining

·        Data mining Applications


Databases

 

·        Bioinformatics

·        Biometrics

·        Image Analysis

·        Financial Modeling

·        Forecasting, Classification, Clustering Cryptography and Information security

·        Social Networks, Educational Data Mining


Big Data

 

·        Big Data Algorithms

·        Big Data Fundamentals

·        Infrastructures for Big Data

·        Big Data Management and Frameworks

·        Big Data Search

·        Big Data security

·        Big Data Applications

·        Data Mining & Machine learning Tasks

·        Machine Learning Applications

·        Learning in knowledge-intensive systems

·        Learning Methods and analysis

·        Learning Problems


Deep Learning

 

·        Knowledge Processing

·        Data and Knowledge Representation

·        Knowledge Discovery Framework and Process, Including Pre- and Post-Processing

·        Integration of Data Warehousing

·        OLAP and Data Mining

·        Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge

·        Integrating Constraints and Knowledge in the KDD Process

·        Exploring Data Analysis

·        Statistical Techniques for Generation a Robust

·        Consistent Data Model

·        Interactive Data Exploration / Visualization and Discovery

·        Languages and Interfaces for Data Mining

·        Mining Trends, Opportunities and Risks

 

Paper Submission

 

Authors are invited to submit papers through the conference Submission System by April 25, 2026 . 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 in Computer Science & Information Technology (CS & IT) series (Confirmed).

 

Selected papers from DSML 2026, after further revisions, will be published in the special issues of the following journals

 

·        Machine Learning and Applications: An International Journal (MLAIJ)

·        International Journal of Data Mining & Knowledge Management Process ( IJDKP )

·        International Journal of Database Management System (IJDMS)

·        International Journal of Web & Semantic Technology (IJWesT)

 

Important Dates

·        Submission Deadline : April 25, 2026

·        Authors Notification : June 13, 2026

·        Registration & Camera-Ready Paper Due : June 20, 2026

Contact Us

 

Here's where you can reach us : [email protected] or [email protected]


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