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Matsuo, Tomoko

Associate Professor

Positions

Research Areas research areas

Research

research overview

  • Professor Matsuo's research aims to advance the science and engineering of forecasting, as applied to the Earth’s atmosphere from the ground to near-Earth space environments, while developing fundamental understanding of the predictability of a coupled Earth-Geospace system. Prediction of constantly changing environmental conditions requires a systematic integration of observations with a first-principles models using data assimilation. Data assimilation reduces uncertainties in initial conditions and drivers, extending the predictive capability of numerical models, and is used for designing of future missions and targeting of observations to maximize scientific returns of observing systems. Professor Matsuo's research also focuses on methodological problems, including the development of the development of scalable data assimilation methods for high-dimensional problems, inversion and machine learning techniques to extract relevant geophysical information from large volumes of data.

keywords

  • Atmospheric sciences and space physics, Predictability of geophysical dynamical systems, Data assimilation, Statistical (Machine) Learning

Publications

selected publications

Teaching

courses taught

  • APPM 4510 - Data Assimilation in High Dimensional Dynamical Systems
    Primary Instructor - Fall 2020
    Develops and analyzes approximate methods of solving the Bayesian inverse problem for high-dimensional dynamical systems. After briefly reviewing mathematical foundations in probability and statistics, the course covers the Kalman filter, particle filters, variational methods and ensemble Kalman filters. The emphasis is on mathematical formulation and analysis of methods. Same as APPM 5510, STAT 4250 and STAT 5250.
  • ASEN 1320 - Aerospace Computing and Engineering Applications
    Primary Instructor - Fall 2020 / Spring 2022 / Spring 2023
    Uses problems and tools from Engineering. Teaches techniques for writing computer programs in higher level programming languages to solve problems of interest in Engineering and other domains. Appropriate for students with little or no prior experience in programming.
  • ASEN 4018 - Senior Projects 1: Design Synthesis
    Primary Instructor - Fall 2024
    Focuses on the synthesis of technical knowledge, project management, design process, leadership, and communications within a team environment. Students progress through the design process beginning with requirements development, then preliminary design and culminating with critical design. Offered fall only.
  • ASEN 4057 - Aerospace Software
    Primary Instructor - Spring 2018 / Spring 2019 / Spring 2020
    Provides an overview of prevalent software and hardware computing concepts utilized in practice and industry. Establishes the background necessary to tackle programming projects on different computing platforms with various software tools and programming languages.
  • ASEN 5018 - Graduate Projects I
    Primary Instructor - Fall 2022 / Spring 2023
    Exposes MS and PhD students to project management and systems engineering disciplines while working a complex aerospace engineering project as part of a project team. The project team may perform some or all of the following project activities during this first semester of the two-semester course sequence: requirements, definition, design and design review, build, test, and verification. Recommended prerequisite: ASEN 4138 or ASEN 5148 or ASEN 5158 or instructor consent required.
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