Emerging Trends in Data Science Theory and Multidisciplinary Applications
This special session is organised and supported by the following educational partners
Prince Sultan University and Taibah University, Saudi Arabia
Session Chair:
Dr. Liyakatunisa Syed, Taibah University, Madinah, Saudi Arabia
Prof. Tanzila Saba, Prince Sultan University, Riyadh, Saudi Arabia
Session Co-Chairs:
Dr Amjad Rehman, Prince Sultan University, Riyadh, Saudi Arabia
Dr Hoshang Kolivand, Liverpool John Moores University, Liverpool, United Kingdom
Synopsis:
Data science is a complex blend of several disciplines including technology, algorithm development, systems and workflows used to obtain insights from data. The enormous emerging progresses and applications of Data Science have been witnessed in a broad range of interdisciplinary and multidisciplinary fields that has high impact on applied and theoretical research areas like machine learning, artificial intelligence, big data analytics, image processing, pattern recognition, search engines, medical informatics, digital economy, robotics, finance, digital humanities, social sciences, text mining, security, IoT, smart education environment, crowd management, forensic, speech recognition and business intelligence and health care. Data Science is a rich family of learning methods, including classification, dimensionality reduction, anomaly detection, Recommender Systems, pattern recognition, sampling, regression, and discriminative analysis. The promising progress has been observed in Data Science due to the emerging techniques of social computing, big data and deep learning. By now, the great number of research output has been obtained, showing the continued booming and productive research of data science, machine learning, artificial intelligence and their applications. This special session aims to bring together the researchers to highlight the significant multidisciplinary scientific problems and major societal issues related to Data Science, Machine Learning & AI, particularly, to address the above-mentioned domains and their recent trends, advances and possible challenges.
Topics:
Topics of interest include, but are not limited to:
- Data Science Trends & Challenges
- Applications of Data Science
- Machine Learning for Intelligent Systems
- Business Analytics
- Data Visualisation
- Image Informatics
- Bioinformatics
- Personalised Medicine
- Networks and Marketing
- Digital Humanities
- Information Security
- Data/Web mining
- Machine Learning & Deep Learning
- Big Data, cloud computing and data-intensive systems
- Innovative data-intensive applications such as health, energy, transport, food and water.
Paper Submission
Prospective authors are invited to submit full-length papers (not exceeding 6 pages) conform to the IEEE format . All papers will be handled and processed electronically via the EDAS online submission system