1. Educational Background (in reverse chronological order)：

• 1997: Tokyo Institute of Technology, Graduate School of Science and Engineering, Computational Engineering, Doctor of Engineering (PhD by Dissertation)
• 1986–1988: Tokyo Institute of Technology, Graduate School of Science and Engineering, Information Science, Master of Science (Full-time)
• 1982–1986: Tokyo Institute of Technology, Faculty of Science, Information Science, Bachelor of Science (Full-time)

2. Work Experience (in reverse chronological order)：

• 2026–Present: Shenzhen Loop Area Institute (SLAI), Professor
• 2025/01–2025/12: The Institute of Statistical Mathematics (ISM), Professor (Full-time)
• 2011/04–2024/12: The Institute of Statistical Mathematics (ISM), Professor (Full-time); Director-level roles
• 2010/04–2011/03: The Institute of Statistical Mathematics (ISM), Professor and Vice Director (Full-time)
• 2008/04–2010/03: The Institute of Statistical Mathematics (ISM), Professor (Full-time)
• 2003/01–2008/03: The Institute of Statistical Mathematics (ISM), Associate Professor (Full-time)
• 2003/01–2003/03: Georgia Institute of Technology (USA), Visiting Associate Professor
• 2001/01–2001/06: Bell Laboratories, Lucent Technologies (USA), Visiting Researcher
• 2000/04–2001/06: Kansai University, Lecturer (Part-time)
• 1998/11–2002/12: ATR, Principal Researcher (Full-time)
• 1988/04–1998/10: NTT, Researcher (Full-time)

Tomoko Matsui, PhD (Engineering), is a Professor at the Shenzhen Loop Area Institute (SLAI). She received her PhD in Information Science from Tokyo Institute of Technology. Her research interests include statistical machine learning, speech information processing, and spatio-temporal data analysis, with applications to climate risk, social sensing, and healthcare. She has published over 100 peer-reviewed papers in leading journals and conferences such as IEEE Transactions, Speech Communication, Spatial Statistics, ICASSP, and Interspeech. Her work has been supported by numerous competitive research grants. She welcomes international collaboration and applications from motivated students, particularly in AI and healthcare, including dementia-related research.

1. Representative Publications (past 5-10 years, in order of impact)：

Murakami D., Peters G. W., Septier F., Matsui T., Generalised Hyperbolic State Space Models with Application to Spatio-Temporal Heat Wave Prediction, Spatial Statistics, 2023 (SCI Q1) 

Feng Z., Markov K., Saito J., Matsui T., Neural Cough Counter: A Novel Deep Learning Approach for Cough Detection and Monitoring, IEEE Access, 2024 (SCI Q1) 

Tran V., Septier F., Murakami D., Matsui T., Spatial-Temporal Temperature Forecasting Using Deep-Neural-Network-Based Domain Adaptation, Atmosphere, 2024 (SCI) 

Shevchenko P. V., Murakami D., Matsui T., Myrvoll T. A., Impact of COVID-19-Type Events on the Economy and Climate under the Stochastic DICE Model, Environmental Economics and Policy Studies, 2021 (SSCI) 

Gao S., Bagnarosa G., Peters G. W., Ames M., Matsui T., A Dynamic Stochastic Integrated Climate–Economic Spatiotemporal Model for Agricultural Insurance Products, North American Actuarial Journal, 2023 (SSCI) 

Tran V., Matsui T., COVID-19 Case Prediction Using Emotion Trends via Twitter Emoji Analysis: A Case Study in Japan, Frontiers in Public Health, 2023 (SCI) 

Murakami D., Matsui T., Improved Log-Gaussian Approximation for Over-Dispersed Poisson Regression: Application to Spatial Analysis of COVID-19, PLOS ONE, 2022 (SCI) 

Azzaoui N., Matsui T., Murakami D., Data-Driven Framework for Uncovering Hidden Control Strategies in Evolutionary Analysis, Mathematical and Computational Applications, 2023 (SCI) 

Tanuma I., Matsui T., Rating Proportion-Aware Binomial Matrix Factorization for Collaborative Filtering, IEEE Access, 2023 (SCI Q1) 

Peters G. W., Nevat I., Nagarajan S. G., Matsui T., Spatial Warped Gaussian Processes: Estimation and Efficient Field Reconstruction, Entropy, 2021 (SCI Q2) 

Murakami D., Kajita M., Kajita S., Matsui T.,
Compositionally-Warped Additive Mixed Modeling for a Wide Variety of Non-Gaussian Spatial Data, Spatial Statistics, 2021 (SCI Q1) 

2. Books/Monographs：

Theoretical Aspects of Spatial-Temporal Modeling, SpringerBriefs in Statistics, 2015, Editor

Modern Methodology and Applications in Spatial-Temporal Modeling, SpringerBriefs in Statistics, 2015, Editor

Speech and Music Emotion Recognition Using Gaussian Processes, In Modern Methodology and Applications in Spatial-Temporal Modeling, Springer, 2015, Co-author

3. Patents：

Acoustic Signal Analyzer and Method, JP Patent 2017-167347, 2017, Co-inventor

Speaker Adaptation Method for Speech Recognition Systems, US Patent 5,835,890, 1999, First Inventor

Speaker Recognition Method and Apparatus, US Patent 5,721,808, 1998, First Inventor

4. Research Awards：

2018: Best Research Presentation Award, National Conference on Collaborative Research and Presentation (CSIS DAYS 2018), Co-recipient

2018: Awaya Kiyoshi Academic Encouragement Award, Acoustical Society of Japan, Co-recipient

1993: IEICE Best Paper Award, Institute of Electronics, Information and Communication Engineers (IEICE), First Author