Arsalan Rahimabadi is a Ph.D. candidate in the Electrical and Computer Engineering Department at Concordia University. His current research is focused on modeling tauopathy progression in the brain. He has expertise in dynamical systems analysis, pathological nonlinear systems, modeling, identification, control theories, and fault detection and isolation methods.
He received his M.Sc. degree in Electrical Engineering – Control as the first-ranked student (out of 26) from K. N. Toosi Univ. of Tech. which is the industrial control center of excellence (ICCE) of Iran, and his B.Sc. degree in Electrical Engineering – Control as the first-ranked student (out of 114) of my faculty from Shahrood Univ. of Tech., Iran.
Since Sep. 2019, he has been a researcher at PERFORM Centre (Montreal). From Jun. 2017 to Sep. 2019, he was the director of dynamical systems analysis and control team of Advanced Robotics and Automated Systems (ARAS) Research Group, Tehran, Iran. From Mar. 2013 to Apr. 2017, he was a researcher at ARAS Research Group.
According to World Alzheimer Report, dementia has affected the lives of over 50 million people around the world, and this figure can rise threefold by 2050. Currently, dementia imposes a cost of trillion dollars annually, and if no cure is found, this figure can be doubled by 2030. The most prevailing form of dementia is Alzheimer's disease (AD). AD belongs to a group of neurodegenerative diseases known as tauopathies characterized by tau protein aggregation. Thus, we aim to address one of the crucial open problems concerning dementia, which is modeling tauopathy progression in the brain.
First discovered in 1975, tau is a microtubule-associated protein (MAP) in the neuron, which many researchers have extensively studied its function to stabilize microtubules and encourage axonal prolongation. This protein is natively unfolded, and in physiological conditions its tendency for aggregation is low. However, there are modifications, such as phosphorylation, which may enable tau proteins to make aggregates. The mechanisms and pathways by which tau protein forms aggregates in tauopathies are not sufficiently comprehended. Hence, our first step is to model the aggregation process of tau. Furthermore, since it has been experimentally proved that these aggregates do not remain in a specific part of the brain and they can spread all over the brain by axonal transportation, we also need to consider the diffusion process in our models. To accomplish our goal, we will take advantage of dynamical systems and control theories to analyze the proposed models.
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