MRI R&D, Sequence Design, Image Reconstruction and Image Processing, Ultra High Field (5T).

Deliverables: Received the "Intent to Award" of NIH/NIA R43/R44 SBIR grant ($500k) as Principal Investigator (PI). Significantly contributed to securing a $420k private seed-fund. Filed one patent (PCT/US2023/014674). • Developed an integrated medical device prototype that combines our customized automated software platform with neuroimaging (EEG) and neuromodulation (tES) devices. This innovative solution offers a non-invasive, portable, and cost-effective approach for the accurate diagnosis and treatment of Depression and AD in an at-home or in-community setting.• Ensured smooth operations of the company while proactively reaching out to collaborators and potential partners in industry, research institutions, and hospitals, to foster and expand our relationships, driving growth and innovation.

Deliverables: Best Dissertation Award (First Place, 1/101), 8 first-authored journal publications, 2 corresponding-authored journal publications, and 10 co-authored journal publications.• Designed physiological experiments to investigate the behavioral psychology related to human behaviors and diseases.• Developed advanced two-level hierarchical Bayesian algorithms to solve inverse problem to increase the spatiotemporal resolution of EEG source localization by utilizing fMRI and fNIRS data as constraints. • Enhanced the classification of large-scale brain network dynamics in emotion processing and regulation by solving the inverse problem and applying an unsupervised K-means machine learning algorithm.• Developed optimization algorithms based on network control theory and Pontryagin minimization principle, designed to optimize stimulation targets and parameters simultaneously for the personalized neuromodulation treatments for depression.