Linxing Preston Jiang

👋 Hi

My name is Linxing (Preston) Jiang (姜麟星, jiāng línxīng). I’m a co-founder and CTO at Mindmorphic, building foundation models for neural recordings.

I received my PhD in Computer Science from the University of Washington, advised by Rajesh Rao. I’m from Harbin, China.

🧠 Research interest

My main research interest is computational neuroscience. I am broadly interested in topics such as predictive coding theories, large-scale neural data pretraining, and bi-directional brain-computer interfaces.

news

Jun 06, 2026	I have successfully defended my PhD dissertation titled Inferring Spatiotemporal Structure through Self-Supervised Learning: From Predictive Coding to Neuro Foundation Models.

selected publications

COLM Workshop

Data Heterogeneity Limits the Scaling Effect of Pretraining in Neural Data Transformers

Linxing Preston Jiang, Shirui Chen, Emmanuel Tanumihardja, and 4 more authors

Conference on Language Modeling (COLM) Workshop on Large Language Modeling for Scientific Discovery (LM4Sci), Oct 2025

Bib HTML

@article{jiang2025pretrain,
  author = {Jiang, Linxing Preston and Chen, Shirui and Tanumihardja, Emmanuel and Han, Xiaochuang and Shi, Weijia and Shea-Brown, Eric and Rao, Rajesh P. N.},
  journal = {Conference on Language Modeling (COLM) Workshop on Large Language Modeling for Scientific Discovery (LM4Sci)},
  title = {Data Heterogeneity Limits the Scaling Effect of Pretraining in Neural Data Transformers},
  year = {2025},
  month = oct,
}

PLOS CB

Dynamic predictive coding: A model of hierarchical sequence learning and prediction in the neocortex

Linxing Preston Jiang, and Rajesh P. N. Rao

PLOS Computational Biology, Feb 2024

DOI Bib HTML

@article{jiang2024dpc,
  doi = {10.1371/journal.pcbi.1011801},
  author = {Jiang, Linxing Preston and Rao, Rajesh P. N.},
  journal = {PLOS Computational Biology},
  publisher = {Public Library of Science},
  title = {Dynamic predictive coding: A model of hierarchical sequence learning and prediction in the neocortex},
  year = {2024},
  month = feb,
  volume = {20},
  pages = {1-30}
}