Delshad Vaghari is a post-doctoral research associate working at the Adaptive Brain Lab. His research uses machine/deep learning to study neurodegenerative diseases. His main interests are the interface of AI and brain sciences. He is also interested in the use of a broad range of neuroimaging techniques (MEG, MRI, PET, etc) to study dementia.

Delshad completed a BSc in BioMedical Engineering followed by an MSc in Signal Processing. He was awarded his PhD in Machine Learning and Pattern Recognition in 2022, supervised by Professor Rik Henson (MRC-CBU, U. of Cambridge) and Professor Ehsanollah Kabir (Tarbiat Modares Univesity). His PhD work introduced a novel Machine Learning framework to combine MEG and MRI to classify MCI patients showing that MEG adds beyond structural MRI. As a part of his PhD, Delshad investigated MEG biomarkers for MCI. The project also published the largest available MEG dataset to study dementia - the BioFIND dataset.

Delshad enjoys spending time with family, gardening, going skiing, and playing backgammon!