Computer and Mathematical Sciences

Mathematical Informatics A05

  • Prof. Masayuki Ohzeki      
  • Assoc. Prof. Kazue Kudo    
  • Assis. Prof. Yoshihiko Nishikawa
  • Assis. Prof Madoka Kobayashi
KeywordsQuantum Computing, Quantum Annealing, Information statistical mechanics, Machine learning, Sparse modeling, Quantum Machine learning

Always something new and unique. Reliable algorithms, reliable applications by information processing and statistical mechanics

Taking a theoretical research style in information science, we aim at fostering information processing and statistical mechanics, developing quantum machine learning, and applying quantum computation by utilizing knowledge from mathematical science and physics. In recent years, machine learning, and data science have made remarkable progress. If we take the time to look at the mathematics behind them, rather than just applying them, we often find that the same thing is a transversal concept in different algorithms and different fields. For instance, Neural networks are a concept at the intersection of brain science, machine learning, and statistical mechanics. Computation on a quantum computer, called a quantum random circuit, is organically related to many issues such as quantum mechanics and gravity, the structure of space-time, computational quantity theory, etc., and can be understood through tensor networks. This understanding is the wellspring from which useful, realistic, and new methods can be created in the end. Every field comes down to the same shaped problem in front of science. We develop the insight to find out where the key issues lie. In addition, with this attitude, we study natural science that is connected to society and philosophy that is useful to society. You will write papers, give presentations at conferences, and use your experience and research results to establish startups, collaborate with others, and even collaborate with large corporations in industry and academia.
Wouldn't you like to have an experience like no other?