Amir Hussain obtained his BEng and PhD from the University of Strathclyde in Glasgow. Following a Research Fellowship at the University of Paisley and a research Lectureship at the University of Dundee, he joined the University of Stirling in 2000, where he is currently Professor of Computing Science and founding Director of the Cognitive Big Data Informatics (CogBID) Laboratory.
His research interests are multi-disciplinary with a focus on brain-inspired, multi-modal cognitive big data technology for solving complex real world problems.
What does this new journal bring to the world of big data? Was something missing from the field, which needed representation?
That’s a good question. This exciting journal fills a growing niche in big data science, specifically addressing the ‘grand question’ of how to make sense of the big data around us, everywhere. A related, underlying question relates to what constitutes Big Data itself.
As part of its vision, the journal will underline the importance of adopting a flexible and open-ended definition of big data
The journal will fill these gaps by providing a unique open-access cross-disciplinary platform for promoting world-class research, development, and application of intelligent analytics in big data science.
As part of its vision, the journal will underline the importance of adopting a flexible and open-ended definition of big data, one that can appropriately scale with time to continually meet the expectations of our multi-disciplinary audience.
What topics can we expect to see?
Topics are expected to cover the whole gamut of big data science, spanning the life, medical, social, engineering, physical, and mathematical sciences, and will solicit the full range of theoretical, computational, algorithmic, experimental, and integrative analytical approaches, together with architectures, implementations, platforms, and their real-world applications – across all relevant disciplines.
Are there any renowned names working on material for the journal/ who have already contributed material for the journal?
The journal has a world-leading Advisory Board, comprising some of the most renowned names from industry and academia, for providing strategic advice regarding the journal’s future directions. The Editorial Board comprises highly distinguished multi-disciplinary researchers whose expertise covers a wide range of research fields related to big data analytics.
Several editors are currently working on developing pioneering material for the journal whilst others have already contributed invited papers – three of these have been published for the journal’s launch.
Several editors are currently working on developing pioneering material for the journal whilst others have already contributed invited papers – three of these have been published for the journal’s launch.
Timothy Wells articulates a case for leveraging big data in population health management. Shu Cheng presents a comprehensive survey of data science with population-based algorithms. Finally, Junaid Qadir highlights the potential of exploiting cutting-edge big data techniques and applications for development of society.
What are your main hopes for the journal?
Our key aspirations for the journal are two-fold and complementary: first, to become a focal point for bringing together the diverse and somewhat disparate big data science research communities, to help them better understand each other, including through standardized big data terminologies, concepts, and sharing of ideas and resources.
This continual cross-fertilization of the various research communities will lead to fulfilment of our second aspiration for the journal, which is to radically promote, initiate, and advance internationally-leading cross-disciplinary big data science analytics research, for serving humanity.
As part of our vision for this exciting journal, we will actively reach out to all stakeholders, including through annual open community consultations, to ensure our scope, publications, and future directions are fully relevant and aligned to meeting the wide expectations of our multi-disciplinary audience – in this emerging era of big data analytics.
Joseph Hasan
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