Triet M. Tran

Triet M. Tran

Ph.D. Candidate

About Me

I am a Ph.D. candidate at the Data Science and Analytics Institute at the University of Oklahoma (OU). My research primarily focuses on developing data analytics methods for neuroimaging datasets, particularly functional MRI (fMRI) and EEG. I am especially interested in statistical physics-based methods, such as the pairwise maximum entropy model, and their applications in computational neuroscience.

Awards, Fellowships, & Grants

2024

  • OU College of Engineering Scholarship, Gallogly College of Engineering (August)
  • Gilbert Ludeman Memorial Scholarship, University of Oklahoma (August)
  • OU GCoE Graduate Student Travel Award, Gallogly College of Engineering (July)
  • Robberson Travel Grant, The Graduate College (June)
  • IEEE EMBC NextGen Scholar Award, IEEE EMBC 2024 (May)

2023

  • Robberson Travel Grant, The Graduate College (October)

Publication

In Preparation

  • Triet M. Tran and Sina Khanmohammadi. “High-Order Energy Landscapes Predict Post-Operative Working Memory Decline in Brain Tumor Patients.”

  • Triet M. Tran, Seyed Majid Razavi, Steven E. Wilson, and Sina Khanmohammadi. “Energy Landscape Analysis of fMRI Reveals Disruptions in Neural Adaptability of Multiple Sclerosis Patients.”

  • Triet M. Tran and Sina Khanmohammadi. “Continuous Energy Landscapes for Discovering High-Order Brain State Transitions.”

Accepted

  • Seyed Majid Razavi, Triet M. Tran, and Sina Khanmohammadi. “Brain State Transition Disruptions in Alzheimer’s Disease: Insights From EEG State Dynamics.” 2025 IEEE International Symposium on Biomedical Imaging (ISBI), IEEE, 2025.

Published

  • Triet M. Tran, Thi T. Tran, and Sina Khanmohammadi. “High-Order Resting-State Functional Connectivity is Predictive of Working Memory Decline After Brain Tumor Resection.” 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, 2024.

Presentations

  • Triet M. Tran, Thi T. Tran, and Sina Khanmohammadi. “High-Order Resting-State Functional Connectivity is Predictive of Working Memory Decline After Brain Tumor Resection.” Poster presentation: Poster Fair & Networking Event, University of Oklahoma, OK. (November 1st, 2024)

  • Triet M. Tran, Thi T. Tran, and Sina Khanmohammadi. “High-Order Resting-State Functional Connectivity is Predictive of Working Memory Decline After Brain Tumor Resection.” 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL. (July 15th, 2024)

  • Matthew Beattie, Triet M. Tran. (2023). “A clustering and machine learning approach to identification of structural drivers of unsheltered homelessness.” Poster presentation: The Computational Social Science Society of the Americas (CSS2023), Santa Fe, NM. (November 4th, 2023)

Teaching Experience

  • 2023-Current: Professional Practicum, Teaching Assistant
  • Aug 2022: DSA Club, Guest Talk

Service and Outreach

  • 2021-2022: DSA Club, Chairman
  • 2021-2022: VSA Student Organization, Volunteer Member

Skills

  • Machine Learning / Deep Learning: GNNs, GCN, LSTM, GRU, etc.
  • Neuroimaging Analysis: Data Preprocessing, Multivariate Pattern Recognition, Network Models, Statistical Physics Models.
  • Programming Languages: Python, R.
  • Databases: SQLite, BigQuery, PostgreSQL, MySQL.

Feel free to explore my work, and if you are interested in collaboration, feel free to reach out!