Mingjian He
Postdoctoral Scholar at Stanford University
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMingjian He is a postdoctoral scholar at Stanford with six years of experience applying multimodal imaging and cognitive neuroscience to preclinical Alzheimer’s research, combining a PhD in Biomedical Engineering from MIT with MS and ScB degrees from Brown. His work spans fMRI, high-density and ERP-EEG, pupillometry, and sleep polysomnography to probe locus coeruleus–noradrenergic signaling, cognitive reserve, and early AD biomarkers. He has led thesis-scale projects on sleep changes in aging and contributed backend fixes and reliability improvements to the widely used PsychoPy experiment platform, underscoring hands-on computational and experimental rigor. Based in Palo Alto, he bridges signal-processing methods and experimental design to translate neurophysiological signals into clinically meaningful markers.
6 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD, Biomedical/Medical Engineering, Doctor of Philosophy - PhD, Biomedical/Medical Engineering at Massachusetts Institute of TechnologyMaster of Science - MS, Cognitive Science, Master of Science - MS, Cognitive Science at Brown UniversityHigh School, High School at Suzhou High SchoolHigh School, High School at Dulwich College International High School
English, Chinese, Spanish
Github Skills (10)
pep10
debug10
python10
psych9
experiment9
neuroscience8
psychopy8
graphical-user-interface7
human-interface7
user-interface7
Programming languages (7)
Github contributions (5)
psychopy/psychopy
May 2024 - Nov 2024
For running psychology and neuroscience experiments
Role in this project:
Back-end Developer
Back-end DeveloperContributions:22 reviews, 58 PRs, 91 comments in 6 months
Contributions summary:Mingjian primarily focused on bug fixes and code improvements within the PsychoPy project. Their contributions involved correcting errors in the preferences dialog and the audio backend, as well as updating code to adhere to PEP8 style guidelines. The user also refactored the handling of sound devices and audio playback, ensuring correct device indexing and improving the reliability of audio playback. Additionally, the user made changes to the eyetracking record component and the movie component for a more reliable and seamless user experience.
neurosciencepythonexperiment-controlcognitive-scienceopenscience
mh105/somata
Dec 2021 - Nov 2022
State-space Oscillator Modeling And Time-series Analysis (SOMATA) is a Python library for state-space neural signal processing algorithms developed in the Purdon Lab.
Contributions:11 releases, 8 commits, 39 pushes in 11 months
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