MA Qi (马琦)
Research Assistant, Cognomics Lab, Zhejiang Uni.
🌐 Academic homepage · 🧠 Cognomics Lab · ✉️ Email
I work at the intersection of computational neuroscience, structural neuroimaging, brain hemispheric lateralization, and generative modeling. I build reproducible research workflows and software for interpretable neuroimaging analysis.
Computational neuroscience, structural MRI, hemispheric asymmetry, cross-hemisphere reconstruction, generative models, statistical learning, and research software.
- Cross-Hemisphere Reconstruction-Derived Neuroanatomical Specificity in Schizophrenia: Multicenter structural MRI analysis of 948 participants across five sites using ANS and RNS. The study examines multiscale group differences, clinical and cognitive associations, and disease classification; the manuscript is in preparation.
- Cross-hemisphere reconstruction and handedness: Evaluating whether reconstruction residuals capture distributed structural information related to handedness beyond conventional gray-matter asymmetry indices. In preparation.
- Operator-corrector validation of residual measures: Testing operator-corrected residual measures across demographic, behavioral, and disease-related settings. In preparation.
- HemiSpec: An installable toolkit for hemispheric-specificity measures, bilateral reconstruction, ROI export, and validation workflows.
- Cortex Visualization Skill and Subcortex Visualization Skill: Reproducible atlas-based cortical and subcortical visualization workflows.
- DecodeWM: Working-memory load prediction with HCP task-fMRI data and machine-learning models.
- LorewormGu: A from-scratch language-model implementation covering pretraining, supervised fine-tuning, and reasoning-format distillation.
I write about brain science, computational neuroscience, NeuroAI, research tools, and reproducible workflows on my public WeChat channel 阿瞒的脑洞 (A Man's Brainhole).
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Read the Writing section on my academic homepage
- Zhejiang University, B.S. in Psychology (2021-2025).
- TOEFL iBT: 5/6 (100/120).
- Python, PyTorch, machine learning, deep learning, structural and task-fMRI analysis, neuroimaging visualization, statistical modeling, reproducible research software, Git/GitHub, and LaTeX.
