Publications

• Data-Efficient Neural Training With Dynamic Connectomes
  Yutong Wu, Peilin He, Tananun Songdechakraiwut
  arXiv:2508.06817 [q-bio.NC], 2025.
  [arXiv]

• Topological and Geometric Signatures of Brain Network Dynamics in Alzheimer’s Disease
  Luopeiwen Yi, Michael Lutz, Yutong Wu, Yang Li, Tananun Songdechakraiwut
  Alzheimer’s & Dementia, 2025.
  [Open Access]

• Functional Connectivity Graph Neural Networks
  Yang Li, Luopeiwen Yi, Tananun Songdechakraiwut
  arXiv:2508.05786 [cs.NE], 2025.
  [arXiv]

• Augmenting Bias Detection in Large Language Models Using Topological Data Analysis
  Keshav Varadarajan, Tananun Songdechakraiwut
  arXiv:2508.07516 [cs.CL], 2025.
  [arXiv]

• LLMs for Longitudinal Clinical Prediction
  Tananun Songdechakraiwut, Michael Lutz

• Functional Connectomes of Neural Networks
  Tananun Songdechakraiwut, Yutong Wu
  AAAI '25 Association for the Advancement of Artificial Intelligence Conference, 2025.
  [Proceedings] [arXiv] [Code] [Talk] [Poster]

• Topological Learning for Brain Networks
  Tananun Songdechakraiwut, Moo Chung
  Annals of Applied Statistics, 2023.
  [PDF] [arXiv] [Code]

• Wasserstein Distance-Preserving Vector Space of Persistent Homology
  Tananun Songdechakraiwut, Bryan Krause, Matthew Banks, Kirill Nourski, Barry Van Veen
  MICCAI '23 International Conference on Medical Image Computing and Computer Assisted Intervention, 2023.
  [arXiv] [Poster]

• Topological Continual Learning with Wasserstein Distance and Barycenter
  Tananun Songdechakraiwut, Xiaoshuang Yin, Barry Van Veen
  NeurIPS '22 on Meta-Learning, 2022.
  [arXiv]

• Fast Topological Clustering with Wasserstein Distance
  Tananun Songdechakraiwut, Bryan Krause, Matthew Banks, Kirill Nourski, Barry Van Veen
  ICLR '22 International Conference on Learning Representations, 2022.
  [PDF] [Review] [Code] [Talk] [Poster]

• Topological Classification in a Wasserstein Distance Based Vector Space
  Tananun Songdechakraiwut, Bryan Krause, Matthew Banks, Kirill Nourski, Barry Van Veen
  NeurIPS '22 on Medical Imaging meets NeurIPS, 2022.
  [PDF]

• Learning to Continually Learn with Topological Regularization
  Tananun Songdechakraiwut, Xiaoshuang Yin, Barry Van Veen
  NeurIPS '22 on Symmetry and Geometry in Neural Representations, 2022.
  [PDF]

• Scalable Vector Representation for Topological Data Analysis Based Classification
  Tananun Songdechakraiwut, Bryan Krause, Matthew Banks, Kirill Nourski, Barry Van Veen
  NeurIPS '22 on Symmetry and Geometry in Neural Representations, 2022.
  [PDF]

• Topological Learning and Its Application to Multimodal Brain Network Integration
  Tananun Songdechakraiwut, Li Shen, Moo Chung
  MICCAI '21 International Conference on Medical Image Computing and Computer Assisted Intervention, 2021.
  [PDF] [Review] [Slides] [Poster]

• Statistical Analysis of Dynamic Functional Brain Networks in Twins
  Moo Chung, Shih-Gu Huang, Tananun Songdechakraiwut, Ian C Carroll, H Hill Goldsmith
  arXiv:1911.02731 [stat.AP], 2020.
  [PDF]

• Dynamic Topological Data Analysis for Functional Brain Signals
  Tananun Songdechakraiwut, Moo Chung
  IEEE ISBI '20 International Symposium on Biomedical Imaging, 2020.
  [PDF]