Kazufumi Ito
· Professor, MathematicsNorth Carolina State University · Finance
Active 1963–2025
Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.
About
Kazufumi Ito is a Professor in the Department of Mathematics at North Carolina State University in Raleigh, North Carolina. His research interests include Control and Optimization Theory, Inverse Problems and Stochastic Analysis, Evolution Equations, Applied Functional Analysis, and Theoretical and Numerical Analysis for Solutions to PDEs. He has contributed to various topics such as Backward Stochastic Differential Equations, Nash Equilibrium and game theory, Optimization, Optimal mass transport, and Feedback methods. His work encompasses both theoretical developments and applications in control theory, stochastic differential equations, and related fields, with a focus on advancing mathematical understanding and computational techniques in these areas.
Research topics
- Computer Science
- Artificial Intelligence
- Mathematical analysis
- Mathematics
- Applied mathematics
- Algorithm
- Pure mathematics
- Mathematical optimization
- Physics
Selected publications
Foundations of Computational Mathematics · 2020 · 27 citations
1st authorCorrespondingAbstract In this work, we propose a class of numerical schemes for solving semilinear Hamilton–Jacobi–Bellman–Isaacs (HJBI) boundary value problems which arise naturally from exit time problems of diffusion processes with controlled drift. We exploit policy iteration to reduce the semilinear problem into a sequence of linear Dirichlet problems, which are subsequently approximated by a multilayer feedforward neural network ansatz. We establish that the numerical solutions converge globally in the…
arXiv (Cornell University) · 2019-06-05 · 14 citations
preprintOpen access1st authorCorrespondingIn this work, we propose a class of numerical schemes for solving semilinear Hamilton-Jacobi-Bellman-Isaacs (HJBI) boundary value problems which arise naturally from exit time problems of diffusion processes with controlled drift. We exploit policy iteration to reduce the semilinear problem into a sequence of linear Dirichlet problems, which are subsequently approximated by a multilayer feedforward neural network ansatz. We establish that the numerical solutions converge globally in the $H^2$-no…
Least squares formulation for ill-posed inverse problems and applications
Applicable Analysis · 2021-03-21 · 10 citations
articleCorrespondingIn this paper we propose a least squares formulation for ill-posed inverse problems. For example, ill-posed inverse problems in partial differential equations are those such that a solution of inverse problem exists for a smooth data but it does not depend continuously on data, or there is no solution for inverse problem, e.g. the Cauchy problem for elliptic equations and backward solution of parabolic equations. We develop the least squares formulation in which the sum of equations error over d…
Journal of Computational and Applied Mathematics · 2021 · 8 citations
Regularized Linear Inversion with Randomized Singular Value Decomposition
Springer proceedings in mathematics & statistics · 2020 · 6 citations
1st authorCorresponding
Recent grants
Efficient Numerical Methods for Time-harmonic Acoustic Wave Propagation
NSF · $175k · 2006–2011
Frequent coauthors
- 73 shared
Karl Kunisch
- 21 shared
Weifu Fang
Wright State University
- 21 shared
H. T. Banks
- 20 shared
Franz Kappel
University of Graz
- 17 shared
Zhilin Li
- 17 shared
Bangti Jin
- 17 shared
R.H. Fabiano
University of North Carolina at Greensboro
- 15 shared
Hien Tran
University Hospital Heidelberg
Similar researchers at North Carolina State University
- Resume-aware match score
- Save to shortlist
- AI-drafted outreach
See your match with Kazufumi Ito
PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.
- Free to start
- No credit card
- 30-second signup