International Conference on Information Science and Machine Learning

ICISML

23rd Oct – 24th Oct 2026 Vienna, Austria

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Registration Summary

Conference ICISML

Date 23rd Oct – 24th Oct 2026

Location Vienna, Austria

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

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Total Payable USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Advancements in Information Science +

This track focuses on the latest developments in information science, emphasizing innovative methodologies and frameworks. Researchers are invited to present their findings on how these advancements impact various domains within social sciences and humanities.

SDG 4 SDG 9

02 Machine Learning Applications in Social Sciences +

This session explores the integration of machine learning techniques in social science research. Papers should highlight case studies and applications that demonstrate the effectiveness of these methods in understanding social phenomena.

SDG 10 SDG 16

03 Data Mining Techniques for Knowledge Discovery +

This track aims to discuss advanced data mining techniques that facilitate knowledge discovery in humanities research. Contributions should illustrate how these techniques can uncover hidden patterns and insights from complex datasets.

SDG 9 SDG 11

04 Artificial Intelligence in Information Systems +

This session examines the role of artificial intelligence in enhancing information systems within the social sciences. Papers should address the implications of AI technologies for data management, retrieval, and analysis.

SDG 9 SDG 16

05 Big Data Analytics in Humanities Research +

This track focuses on the utilization of big data analytics to address questions in the humanities. Researchers are encouraged to share their experiences and methodologies in analyzing large datasets to derive meaningful insights.

SDG 4 SDG 9

06 Neural Networks for Predictive Modeling +

This session delves into the application of neural networks for predictive modeling in social science contexts. Submissions should demonstrate how these models can forecast trends and behaviors based on historical data.

SDG 8 SDG 16

07 Ethical Considerations in Data Science +

This track addresses the ethical implications of data science practices in social research. Papers should discuss frameworks and guidelines for ensuring responsible use of data in the context of social sciences and humanities.

SDG 16

08 Interdisciplinary Approaches to Information Science +

This session encourages interdisciplinary research that merges information science with other fields within the social sciences and humanities. Contributions should highlight collaborative efforts and the benefits of cross-disciplinary methodologies.

SDG 4 SDG 17

09 Innovative Data Visualization Techniques +

This track focuses on the development and application of innovative data visualization techniques in social science research. Researchers are invited to present their work on how effective visualization can enhance data interpretation and communication.

SDG 4 SDG 9

10 Challenges in Data Integration and Management +

This session addresses the challenges faced in data integration and management within information systems. Papers should explore strategies for overcoming these challenges to improve data accessibility and usability.

SDG 9 SDG 16

11 Future Trends in Information Science and Machine Learning +

This track speculates on future trends and directions in information science and machine learning as they relate to social sciences. Contributions should provide insights into emerging technologies and methodologies that could shape future research.

SDG 9 SDG 17