The Algorithms, Data, and Artificial Intelligence section conducts cutting-edge research within the fields of algorithms, data-intensive systems, and artificial intelligence. Our work spans foundational theoretical research and applied innovations, driving advances in computation, data analysis, machine learning, and natural language processing.
We study fundamental algorithmic techniques, computational complexity, and game theory to understand the limits of computation and strategic decision-making. Our research also explores the theoretical underpinnings of machine learning, with a focus on clustering, learning accuracy, and explainability. In parallel, we address challenges in modern data management, covering databases, data mining, and large-scale analytics, including deep learning, natural language processing and generative AI.
By bridging theory and practice, we develop efficient algorithms and scalable data solutions for applications ranging from classic database systems to computational economics and AI. Through interdisciplinary projects and industry partnerships, we apply our findings to real-world challenges, ensuring impact across academia and society.
This section is a combination of the Algorithms, Data Structures and Foundations of Machine Learning, Computational Complexity and Game Theory and Data-Intensive Systems research groups
