With 7 years of experience in the field of medical imaging and approaching the end of my current project, I am now seeking my future position.
Coming from an engineering background in image and signal processing, I have specialized in medical imaging and AI through various research projects I have participated in. Working in neuroimaging, I am familiar with acquisition chains, registration issues, normalization, segmentation, as well as linear and statistical modeling of volumetric and surface image series.
From preprocessing pipelines for primate MRI to AI algorithms for cortical sulcus detection, I have leveraged my collaborations to develop tools benefiting multiple teams worldwide. These diverse research endeavors have also led to participation in several international conferences and scientific publications.
Blog
Datasets
Presentations
Posters
Publications
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Browsing Multiple Subjects When the Atlas Adaptation Cannot Be Achieved via a Warping Strategy
- Detection of abnormal folding patterns with unsupervised deep generative models
- A collaborative resource platform for non-human primate neuroimaging
- FMRI-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance
- Accelerating the evolution of nonhuman primate neuroimaging
- Inter-subject pattern analysis: A straightforward and powerful scheme for group-level MVPA
- Single-trial fMRI activation maps measured during the InterTVA event-related voice localizer. A data set ready for inter-subject pattern analysis
- Mapping individual differences in cortical architecture using multi-view representation learning
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