معرفی
Tananun Songdechakraiwut is an Assistant Research Professor of Computer Science at Duke University (2023–Present), affiliated with the Duke Institute for Brain Sciences and Trinity College of Arts & Sciences. A computational neuroscientist and AI researcher, they develop topological methods for analyzing brain networks and enhancing neural network-based AI models.
- Education: Ph.D. in Electrical Engineering and Computer Sciences (EECS), University of Wisconsin–Madison (2023); B.S. in EECS, University of California–Berkeley
Their research focuses on topological data analysis (TDA) for understanding brain network dynamics and applying these insights to improve AI systems. Key contributions include novel frameworks for persistent homology, Wasserstein distance preservation, and dynamic connectome modeling.
Recent publications highlight their work on functional connectomes, topological learning, and brain-inspired AI, with applications in neuroscience, Alzheimer's disease analysis, and medical imaging. They also teach graduate and undergraduate courses in Data Science, Artificial Intelligence, and Computational Connectomics.
- 2024: Recipient of Duke University's Research & Innovation Seed Grant ($2M total)
Tananun mentors semester-long data science projects and integrates topological methods into real-world problem-solving through Duke's Bass Connections in Brain & Society program.
