PhD Candidate, University of Toronto

Engineer | Researcher | Educator

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I’m a PhD candidate in Biomedical Engineering at the University of Toronto in the Intelligent Assistive Technology and Systems Lab, advised by Dr. Alex Mihailidis. I am also working with the Roe Lab in the Knight Alzheimer’s Disease Research Center, Department of Neurology, at Washington University School of Medicine.

My research interests involve using wearable technologies to monitor health in the context of everyday environments. I believe how people interact with their environment reveals significant information about their health and well-being. Through my work, I aim to examine these interactions by using methods from spatial analysis, data mining and artificial intelligence.

In my PhD thesis, I am investigating whether GPS mobility can be used to explain, influence, and/or predict dementia. The two primary projects that I am working on are:

(1) Analyzing mobility patterns of people with dementia using multi-sensor datasets including GPS and accelerometry​

 

(2) Investigating in-road driving performance of people with preclinical Alzheimer's disease using GPS driving data

Before my PhD, I graduated with a bachelor's degree in Engineering Science (Aerospace Major) at the University of Toronto in 2016.

Updates:

6/2021

Very excited to have accepted an assistant professorship at the University of Calgary in the Geomatics Engineering department &  Centre for Bioengineering Research beginning in September 2021.

5/2021

Our paper "GPS Driving: A Digital Biomarker for Preclinical Alzheimer Disease" has been accepted for publication in Alzheimer's Research & Therapy. For more information, check here.

5/2021

Our abstract "Evaluating predictability in outdoor mobility: A potential pathway to personalized assistance for people with dementia" has been accepted for presentation at the AAIC, happening on July 26 - 30th.

 
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GPS Driving: A Digital Biomarker for Preclinical Alzheimer Disease

Sayeh Bayat, Ganesh M. Babulal, Suzanne E. Schindler, Anne M. Fagan, John C. Morris, Alex Mihailidis, Catherine M. Roe

Alzheimer's Research & Therapy 2021 - In Press

We applied machine learning methods to a large dataset of GPS driving trajectories from a cohort of cognitively intact older drivers with and without preclinical AD. Our findings suggest that driving may serve as an effective and accurate digital biomarker for identifying preclinical AD among older adults. 

Paper (to be posted)

Outdoor Life in Dementia: How predictable are people with dementia in their mobility?

Sayeh Bayat and Alex Mihailidis.

Alzheimer's & Dementia: DADM 2021

Aiming to better capture the essence of mobility of people with dementia, we analyze the randomness and predictability manifested in their GPS trajectories. We find that relying on both spatial and temporal patterns,  a 4-week record of mobility patterns of people with dementia displays 95% potential predictability.

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A GPS-based Framework for Understanding Outdoor Mobility Patterns of Older Adults with Dementia: An Exploratory Study

Sayeh Bayat, Gary Naglie, Mark Rapoport, Elaine Stasiulis, Michael J Widener and Alex Mihailidis.

GERONTOLOGY 2021

We develop a comprehensive framework for comparing outdoor mobility patterns of cognitively intact older adults and older adults with dementia using passively collected GPS data.

Paper

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Bringing the ‘Place’ to Life Space in Gerontology Research

Sayeh Bayat, Michael J Widener and Alex Mihailidis.

GERONTOLOGY 2021

We discuss new directions for extending the life-space framework in environmental gerontology by drawing on the advancements in the activity space framework in travel behaviour and health geography literature.

Paper

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Inferring Destinations and Activity Types of Older Adults From GPS Data: Algorithm Development and Validation

Sayeh Bayat, Gary Naglie, Mark Rapoport, Elaine Stasiulis, Belkacem Chikhaoui and Alex Mihailidis.

JMIR AGING 2020

We develop and validate a framework that relies solely on GPS data to capture older adults’ travel destinations (ie, stop points) and activity types. We show that GPS technology can be used to extend the traditional life-space assessments by accurately determining semantic dimensions of outdoor mobility.

Paper 

 

A High-Performance Millirobot for Swarm-Behaviour Studies: Swarm-Topology Estimation

Justin Y Kim, Zendai Kashino, Laura Marcela Pineros, Sayeh Bayat, Tyler Colaco, Goldie Nejat, Beno Benhabib

IJARS 2019

We present a novel high-performance millirobot ( milli- robot- Toronto), designed to allow for the testing of complex swarm-behaviours, including human–swarm interaction. As complementary software to this hardware development, we also present a new global swarm-topology estimation algorithm. 

Paper 

MIE1624: Introduction to Data Science and Analytics

  • Tutorial Teaching Assistant, Mechanical & Industrial Engineering Department, graduate course, (~100 students)

MIE1622: Computational Finance & Risk Management

  • Tutorial Teaching Assistant, Mechanical & Industrial Engineering Department, graduate course, (~70 students)

MAT188: Linear Algebra & MATLAB

  • Head Teaching Assistant, Core Course, First-year Engineering, (~800 students)​

APS106: Foundations of Computer Programming (Python)

  • Computer Lab Teaching Assistant, Core Course, First-year Engineering, (~800 students)

CSC108: Introduction to Computer Programming (Python)

  • Office Hour & Marking Teaching Assistant, Computer Science Department, (~1000 students)

 

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Contact Me

TRI - KITE Research Institute

550 University Ave, Toronto, ON M5G 2A2  

Email: sayeh.bayat@mail.utoronto.ca 

Tel: 416-597-3422 x 7345