🧠Research Scholar
lindu[at]fas.harvard.edu
ldu[at]mit.edu
MEng Computer Science
2023-09-01
2026-07-31
Beijing Normal University | McGovern Institute for Brain Research | Liu Lab
I have had experience in Computational & Cognitive Neuroscience research using Contrastive Deep Learning Methods, Diffusion Models, Reinforcement Learning, Transformer-based Frameworks, LLMs, and Precision fMRI Analysis.
Please reach out to collaborate 😃
The specific neuroanatomy of mild cognitive impairment (MCI) is obscured by its clinical heterogeneity and confounding effects from normative variation. This problem is compounded …
Background and Hypothesis: Schizophrenia (SZ) is a debilitating mental disorder characterized by heterogeneous clinical manifestations and widespread brain structural …
In this study, we established a link between data-driven dynamic organizational modeling (including co-activation pattern and hidden Markov model) and theory-driven neurodynamic …
In this study, we developed a Transformer-based autoencoder (TAE) model for temporal dimensionality reduction of fMRI data, harnessing the Transformer's ability to capture temporal …
Kanwisher Lab, McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT
Buckner Lab, Center for Brain Science, Department of Psychology, Harvard University.
The Organization for Human Brian Mapping, Brisbane, Australia, 2025
The Organization for Human Brian Mapping, Brisbane, Australia, 2025
Liulab, State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University
Lin defended his Master's degree in Computer Science at the McGovern Institute for Brain Research, Beijing Normal University.