The field of AI (Artificial Intelligence) and Data Engineering represents a dynamic and rapidly evolving landscape at the intersection of computer science, mathematics, and engineering. This interdisciplinary domain is dedicated to advancing the capabilities of machines to simulate human intelligence and to harness the power of data for decision-making and problem-solving.

The emergence of machine learning as a cornerstone of AI marked a paradigm shift in how systems could be trained to improve performance over time. Deep learning, a subset of machine learning, gained prominence with the development of neural networks capable of processing vast amounts of data and extracting intricate features. This led to unprecedented achievements in image recognition, natural language processing, and other complex tasks.

In parallel with AI advancements, the role of data became paramount. Data engineering involves the collection, storage, and processing of large volumes of structured and unstructured data. The rise of big data technologies, distributed computing frameworks, and scalable storage solutions enabled organizations to harness the potential of massive datasets.

The synergy between AI and data engineering became evident as AI models required large datasets for training and validation. Data engineering pipelines became crucial for preprocessing, cleaning, and transforming raw data into formats suitable for machine learning algorithms. This convergence led to the development of AI-driven applications with real-world impact, ranging from healthcare and finance to autonomous vehicles and natural language understanding.

Finally, the AI and data engineering field represents a dynamic and interconnected ecosystem where technological innovation, ethical considerations, and real-world applications converge. Researchers and practitioners in this field are at the forefront of shaping the future of intelligent systems, driven by a commitment to advancing knowledge, addressing challenges, and creating positive societal impact.

Vision & Mission

Vision: Become the national hub for artificial intelligence and data engineering research while actively participating at the regional and international levels.

  • Conduct artificial intelligence and data engineering research to enhance the quantity and quality of intellectual property that has impactful commercialization potential.
  • Actively collaborate in the field of artificial intelligence and data engineering to promote international collaboration and recognition.
  • Increase the quantity and quality of impactful international journal publications in the fields of artificial intelligence and data engineering, contributing to the realization of the vision and mission of our faculty and university.

Research Cluster

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