ISFTD Webinar on iPSC and Organoid Models of FTD

This webinar is scheduled for Wednesday, February 25, 2026 at 8:00 AM PST | 11:00 AM EST | 5:00 PM CET.
To see what time this is in your time zone, please click on the following link https://bit.ly/49Rdgkz.

Join us for an exciting webinar showcasing how human stem cell–based models are advancing frontotemporal dementia (FTD) research. This session will focus on induced pluripotent stem cells (iPSCs) and brain organoid models to study FTD pathology, uncover disease mechanisms, and better capture human-specific aspects of neurodegeneration. Speakers will present complementary approaches using human iPS cells and organoid systems, highlighting how these models are opening new avenues for understanding FTD and accelerating therapeutic discovery. 

John F. Crary, US

Mahsa Dadar, CA

Neguine Rezaii, US

John F. Crary

John F. Crary, MD-PhD, is a board-certified neuropathologist and Professor at the Icahn School of Medicine at Mount Sinai. He directs the Neuropathology Brain Bank and leads international efforts defining diagnostic criteria for tauopathies and brain aging. Dr. Crary pioneered AI-driven digital neuropathology, developing tools such as HistoAge to quantify cellular aging in human brain tissue. His research integrates human tissue, molecular pathology, and machine learning to uncover mechanisms of neurodegeneration. He is an international leader advancing the future of precision neuropathology through innovation at the interface of biology and artificial intelligence.

Mahsa Dadar

Mahsa Dadar is an assistant professor at the Cerebral Imaging Centre of the Douglas Research Centre, McGill University. Her work is focused on using neuroimaging and machine learning techniques to investigate the progression and impact of cerebrovascular and neurodegenerative pathologies in aging populations.

Neguine Rezaii

Neguine Rezaii is an Assistant Professor of Neurology at Harvard Medical School and the Director of the Computational Neuropsychiatry Program at the Frontotemporal Disorders Unit at Mass General Hospital. She is interested in the analysis of the rich signal of language through methods in artificial intelligence for early detection and prognostication of various neuropsychiatric disorders.