M-Tahar Kechadi

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Prof M-Tahar Kechadi

Member since: 03/26/2020 - 14:41
Professional title: 
Professor
Primary Domain/Field of Expertise (Other): 
Computer Science/Artificial Intelligence and Data Science
Organization name: 
University College Dublin
Organization type: 
Academia/Research
City: 
Dublin
Country: 
Ireland {Republic}

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Professor M-Tahar Kechadi was awarded PhD and MSc degrees - in Computer Science from University of Lille 1, France. He is currently Professor of Computer Science at School of Computer Science, UCD. He is a PI at the Insight Centre for Data Analytics. He serves on the scientific committees for a number of international conferences and he organised and hosted one of the leading conferences in his area. The core and central focus of his research for the last decade is how to manage and analyse data quickly and efficiently. Nowadays we live in digital world, we produce more data than we can analyse and exploit. This “big data” will continue to grow at rapid pace, will underpin new waves of innovation in nearly every sector of the world economy, and will reshape the way we build and use computers (hardware and software). Currently, my research interests are primary in • Big Data Analytics and its applications to real-world applications. • Big Data Applications: Digital Healthcare and digital agriculture. • Distributed Mining techniques and models and their execution environments and applications. • Digital Forensics and cybersecurity. In big data applications, both the analysis of large datasets and the computing environments created new problems and challenges for efficient execution and optimal system performance. This brought me to look at the challenges of the data analytics in the heterogeneous, complex, distributed environment. Another key objective is to design and develop data analytics techniques that delineate a careful division of work between the user and computer. One way to tackle this challenge is to provide constant feedback to the user and engage with the user only when it is required. And finally, the scalability and privacy issues, as the datasets are becoming extremely large containing data of various types and pertaining to different systems or users. Recently, I am specifically looking at these issues from cybersecurity and data privacy point of view.





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