Algorithm and complexity
The “Algorithms and Complexity” research focuses on the development, analysis, and optimization of algorithms, with a deep emphasis on computational efficiency and resource management. Our work aims to advance the understanding of algorithmic complexity, exploring innovative solutions to computational challenges across various domains.
Computational learning theory
Our “Computational Learning Theory” research is dedicated to studying the theoretical foundations of machine learning, focusing on the design and analysis of algorithms that learn from data with provable guarantees on performance and generalization.
Algorithmic Game Theory
The “Algorithmic Game Theory” research explores the intersection of algorithms, game theory, and economics, focusing on the design and analysis of systems where strategic behavior and computational efficiency converge.
Cryptography and Blockchains
The “Cryptography and Blockchains” research is focused on theoretical advancements in both cryptographic systems and blockchain technologies. We investigate the fundamental principles underlying secure encryption, protocol design, and decentralized consensus, aiming to rigorously analyze and develop new theoretical frameworks that enhance privacy, security, and efficiency in cryptographic methods and blockchain architectures.