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Jiansheng Niu has held a variety of roles in the biosignal and machine learning fields since 2017. In 2021, they began working as a Biosignal Research Engineer for Muse® by Interaxon Inc. From 2019 to 2021, they worked as a BCI software engineer and BCI-ML researcher for the Waterloo Engineering Bionics Lab (eBionics). During this time, they developed a desktop application using Python for physiological data collection, annotation, visualization, and experimentation, and designed and conducted experiments to investigate upper-limb movement intention by collecting EEG and EMG signals. In 2019, they also worked as a BCI researcher for Wilfrid Laurier University, where they conducted experiments on Parkinson's Disease patients and healthy age-matched control groups to collect EEG, EMG, and IMU data. In 2018, they worked as a BCI research engineer for Peking University, where they completed a literature review of classification algorithms for EEG-based BCI design and studied Riemannian geometry from an engineering perspective. In 2017, they worked as a Machine Learning Intern for Texas A&M University, where they built a polynomial regression model to predict 24-hour wind speed in summer based on Lake Winnebago wind speed data.

Jiansheng Niu obtained a Bachelor of Engineering in Electrical and Electronics Engineering from the University of Nottingham in 2018, after studying there from 2014 to 2018. Jiansheng subsequently obtained a Master of Science in Systems Design Engineering from the University of Waterloo in 2021. Additionally, they have obtained certifications in Deep Learning Specialization from Coursera in 2021 and Machine Learning from Coursera Course Certificates in 2018.