Basic Information

Email Address

• Email Address

  phi.tiencuong.6ikyoto-u.ac.jp

Academic Degree

• 08 Jun. 2018

  University of Nice修士（Probability and Statistics）
• 14 Jun. 2022

  University of Nice博士（Probability and Statistics）

Academic Resume (Undergraduate School/Majors)

• Hanoi National University of Education (Vietnam), High School for Gifted Students, 卒業
• Hanoi National University of Education (Vietnam), Dept. Mathematics, Major Mathematics, 卒業

ID,URL

• ORCID ID

  0009-0007-6275-8270

researchmap URL

• https://researchmap.jp/cuongphi

Research

Research Topics, Overview of the research

• Research Topics

  My research integrates computational neuroscience, applied mathematics, information theory, and machine learning to investigate neural dynamics, cognition, and brain functional connectivity, while developing EEG foundation models and personalized neural decoding.

• Overview of the research

  My research focuses on understanding how the brain processes information, learns, and makes decisions by integrating computational neuroscience, applied mathematics, information theory, and machine learning. I analyze neural recordings and brain imaging data, including EEG, fMRI, and calcium imaging, to investigate neural dynamics, functional connectivity, and information integration across brain regions. My current research also focuses on developing EEG foundation models capable of learning transferable neural representations across individuals, tasks, and recording sessions. Additionally, I explore personalized neural decoding and model adaptation to individual differences, aiming to improve the generalizability and reliability of brain–computer interfaces. Ultimately, my goal is to bridge neuroscience and artificial intelligence to advance brain research and clinical applications.

Research Interests

• Computational Neuroscience
• Functional Connectivity
• Foundation Models
• Brain Computer Interfaces

Research Areas

• Life sciences, Neuroscience - general

Papers

• Neural mechanisms of individual differences in prior weight during scene recognition

  Tien Cuong Phi; Kojiro Hayashi; Risa Katayama; Ken Nakae; Shin Ishii

  NeuroImage, Dec. 2025, Peer-reviewed, Lead author, Corresponding author

  
• Integrated information theory reveals the potential role of the posterior parietal cortex in sustaining conditioning responses in classical conditioning tasks

  Tien Cuong Phi; Shin Ishii; Masashi Kondo; Masanori Matsuzaki; Ken Nakae

  Frontiers in Neuroscience, 29 Jan. 2025, Peer-reviewed, Lead author, Corresponding author

  
• Kalikow decomposition for counting processes with stochastic intensity and application to simulation algorithms

  Tien Cuong Phi; Eva Löcherbach; Patricia Reynaud-Bouret

  Journal of Applied Probability, 19 May 2023, Peer-reviewed, Lead author

  
• Kalikow decomposition for counting processes with stochastic intensity

  Tien Cuong Phi

  14 Jun. 2022, Peer-reviewed, Lead author

  
• Event-Scheduling Algorithms with Kalikow Decomposition for Simulating Potentially Infinite Neuronal Networks

  Tien Cuong Phi; Alexandre Muzy; Patricia Reynaud-Bouret

  SN Computer Science, Jan. 2020, Peer-reviewed, Lead author