Main current data science and artificial intelligence advancements and challenges


  • Prof. Dimitrios A. Karras, PhD Canadian Institute of Technology, Faculty of Engineering



Data Science and Artificial Intelligence play a major role in the nowadays fourth industrial revolution of Robotics, Artificial Intelligence and big Data. The purpose of this editorial is to identify the progress, the trends, the open problems and challenges of these research fields in a comprehensive way, so that an overview is provided that would help researchers and practitioners in their research and development orientations. A lot of research and development efforts since many years have brought Data Science and Artificial Intelligence in a good shape and level of maturity. These technologies have proved to be realizable in a wide range of real world applications with considerable success. Although the analytical theories they are based on are not all in mature level, however, their black box implementations have been very promising so far with real improvements in real world systems performance and usability. At this stage of development such an emergent revolution in all aspects of life demands a careful thinking to discriminate hype from real achievements. This is the major goal of this editorial, to start such a discussion since hype has been a serious obstacle, many times at the past, for real technological advancements. Filtering hype and revealing reality in these fields requires much effort and extensive studies in all application fields and it is not possible within this editorial. We plan more publications in depth regarding this issue. This editorial should be considered only as a first small step towards this goal. Starting from current major trends of Data Science and aspects of Artificial Intelligence


Data Science, Artificial Intelligence, 4th Industrial revolution, Technology and Business Trends.


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Author Biography

Prof. Dimitrios A. Karras, PhD, Canadian Institute of Technology, Faculty of Engineering

Prof. Dimitrios A. Karras received his Diploma and M.Sc. Degree in Electrical and Electronic Engineering from NTUA, Greece in 1985 and the Ph.D. in Electrical Engineering, from the NTUA, Greece in 1995, with honors. From 1990 and up to 2004 he collaborated as visiting professor and researcher with several universities and research institutes in Greece. He has published more than 70 research journal papers and more than 185 research papers in International refereed scientific Conferences. His research interests span the fields of intelligent and distributed systems, pattern recognition and computational intelligence, image and signal processing and systems, among others. He has served as program committee member as well as program chair and general chair in several international workshops and conferences. 


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Sophia Aparicio, João Tiago Aparício and Carlos J. Costa, Data Science and AI: Trends Analysis, June 2019, DOI:10.23919/ CISTI.2019.8760820, Conference: 2019 14th Iberian Conference on Information Systemsand Technologies (CISTI). DOI:

Joao Tiago Aparicio, Mario Romao, Carlos J. Costa, “Predicting Bitcoin prices : The effect of interest rate, search on the internet, and energy prices”, 2022 17th Iberian Conference on Information Systems and Technologies (CISTI), pp.1-5, 2022. DOI:

Reihaneh Hajishirzi, Carlos J. Costa, “Artificial Intelligence as the core technology for the Digital Transformation process”, 2021 16th Iberian Conference on Information Systems and Technologies (CISTI), pp.1-6, 2021. DOI:

Carlos J. Costa, João Tiago Aparicio, “POST- DS: A Methodology to Boost Data Science”, 2020 15th Iberian Conference on Information Systems and Technologies (CISTI), pp.1- 6, 2020. webinars/ DOI:




How to Cite

Karras, D. (2022). Main current data science and artificial intelligence advancements and challenges. CRJ, 1(1), 7–10.




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