FUJII Kaito (Assistant Professor)
fujiik (at) nii.ac.jp
Research Keywords : Algorithms, Machine Learning, Combinatorial Optimization
Education and research supervision on the theory and application of combinatorial optimization. In particular, our research focus includes submodular optimization and its applications to machine learning, such as active learning or compressed sensing, and combinatorial optimization frameworks for decision-making under uncertainty, such as adaptive optimization or optimal stopping theory.
HIRAHARA Shuichi (Associate Professor)
s_hirahara (at) nii.ac.jp
Research Keywords : P versus NP Problem, Kolmogorov Complexity, Minimum Circuit Size Problem, Pseudorandomness, Computational Complexity Theory
Computational Complexity Theory has many open questions, such as the P versus NP problem. We aim at understanding the limits of computations. Our research topics include studying the minimum circuit size problem; derandomization and pseudorandomness (the P versus BPP problem), worst-case versus average-case complexity, cryptography, computational learning theory.
KAWARABAYASHI Ken-ichi (Professor)
k_keniti (at) nii.ac.jp
Research Keywords : Algorithms, Graph Theory, Heoretical Computer Science, Discrete Math
Education and research supervision on Discrete Math with special emphasis on Structural Graph Theory and Graph Minor Theory.
We also consider their algorithmic applications. Most likely, the following topics will be covered.
1. Perfect graphs and its applications.
2. The Four Color Theorem and its generalization.
3. Structural Graph Theory.
4. Disjoint paths problem and Network
5. Matching theory and its applications
6. Graph Minor Theory and its applications.
KISHIDA Masako (Associate Professor)
kishida (at) nii.ac.jp
Research Keywords : Networked systems, Uncertain systems, Control theory, Optimization
Students are welcome who are interested in the broad area of control theory and its related areas in applied mathematics such as optimization and linear algebra. My research aims at developing theories and algorithms for systems that are not well-addressed by existing methods. The focus is placed on the systems theory that takes uncertainties into account for the applications to complex systems and networked systems.
MATSUMOTO Keiji (Associate Professor)
keiji (at) nii.ac.jp
Research Keywords : Entanglement, Information theory, Statistics, Quantum information, Quantum computation
It is well-known that quantum mechanical view of the world is quite conter-intuitive.
Indeed, it contradicts with many basic concepts which information sciences are based on. Therefore, it is necessary to built new information sciences to be consistent with quantum mechanics, which is fundamental law of the nature. Recently, it has been found out that quantum information processing has wide range of application to technologically important problems, such as integer factoring, secure communication and so on. In this lecture, starting from basic concepts, we review the recent developments of the field. The audiences of the lecuture are expected to be familiar with elementary linear algebra, probability, and information theory, but no background in quantum mechanics.
SOEDA Akihito (Associate Professor)
soeda (at) nii.ac.jp
Research Keywords : Quantum algorithms, Quantum information theory
The physical systems assumed in the standard models of information processing obey the “classical” theory of physics, but physical systems in fact obey quantum theory. Recently, information processing exploiting quantum properties is being extensively investigated, suggesting that quantum information processing (QIP) may substantially outperform the standard information processing. Current QIP technologies, however, still do not fulfill the requirements imposed by the quantum algorithms proposed so far. QIP technologies are constantly advancing, which simultaneously extends our QIP possibilities. We seek to incorporate these advances and investigate and design quantum algorithms from their foundations to address practically relevant problems.
TATSUTA Makoto (Professor)
tatsuta (at) nii.ac.jp
Research Keywords : Software verification, Programming logic, Lambda calculus, Type theory, Constructive logic
Foundational theory of computer science related to mathematical logic, and mathematical logic for computer science are studied.
1. Type theory (higher order type theory, type inference, Curry-Howard isomorphism, inductive types)
2. Constructive logic (constructive set theory, inductive definitions, realizability interpretations, linear logic)
3. Theory of programs (program verification, program synthesis, program transformation, lambda-calculus)
UNO Takeaki (Professor, Principles of Informatics Research Division)
uno (at) nii.ac.jp
Research Keywords : Algorithms, Data engineering, Data mining, Optimization, Computation
The main topic of the seminar is theoretical fundamentals of discrete algorithms. The sub topics are time and space complexities, extension to general problems of discrete algorithms, especially, fundamental algorithms appearing in optimization algorithms. Studies on efficient applications for practical systems are also researched. The goal is to have knowledge and techniques of general algorithms, not for minor area, and to be able to pertinently research whatever algorithmic problems.
YOKOI Yu (Assistant Professor)
yokoi (at) nii.ac.jp
Research Keywords : Algorithms, Mechanism design, Combinatorial Optimization
Education and research supervision on discrete mathematics, algorithms, and their applications to mechanism design. In particular, we investigate problems in game-theoretic settings, such as the stable matching model. We design algorithms and analyze discrete structures using techniques of combinatorial optimization.
YOSHIDA Yuichi (Professor)
yyoshida (at) nii.ac.jp
Research Keywords : Algorithms, Theoretical Computer Science (Combinatorial) Optimizations
Education and research supervision on theoretically and/or practically efficient algorithms. In particular, our research focus includes (but not limited to) theory and applications of “sublinear algorithms” such as property testing, streaming algorithms, compressed sensing, and theoretical analysis and the development of efficient algorithms, with the theory lens, of optimization problems that arise in practical areas such as machine learning.