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Abeer Badawi, Ph.D. | Postdoctoral in AI & Health | Faculty Affiliate Researcher at Vector Institute | Lecturer in Computer Engineering

About me

Dr. Abeer Badawi is a postdoctoral researcher at York University and a faculty affiliate researcher at Vector Institute, which is supported by the Connected Minds Scholarship (CFREF). She earned her PhD in Computer Engineering at Ontario Tech University supervised by Dr. Khalid Elgazzar in 2024. She received the Ontario Graduate Scholarship and a nomination for the best thesis award for her work on AI-driven prediction of neuropsychiatric symptoms in dementia patients. She has experience in AI research and healthcare applications since 2016 and collaborated with leading organizations such as UHN, Ontario Shores Hospital, University of Toronto, Vector Institute, and Kids Help Phone. Her research focuses on digital biomarkers, machine learning, large language models, responsible AI, and mental health LLM systems evaluation for healthcare applications.  Dr. Badawi is also a lecturer in the computer engineering department at Ontario Tech University. She has teaching experience since 2016 as a teaching assistant and lecturer in two universities in several engineering departments with more than 20 courses. Aside from academia, Dr. Badawi also worked in the industry as a machine learning specialist at Vector Institute and a Data scientist at BetterCart Inc. She was also the president and founder of the IEEE-HKN Mu beta chapter; this chapter allowed her to work as part of a team, make decisions, and help students explore Python and machine learning by providing classes at the university. 

Summary

Projects

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 Leveraging Artificial Intelligence to Detect Neuropsychiatric Symptoms in Patients with Dementia Within Clinical Settings

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Human Activity Recognition From
Wearable Sensors Using Machine Learning and Feature Selection

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​Pre-trained Deep Learning Models for Coronavirus (Covid-19) Prediction from Chest X-ray images

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Real-Time Data Streaming with Apache Kafka and AI for Health Risk prediction of ECG signals

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Character name extraction from movies screenplays nltk

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The Best Neighborhood in Toronto to open a Middle Eastern Restaurant

Work Experience

Teaching Experience

Work Experience

Postdoctoral at York University and Faculty Affiliate Researcher at Vector Institute                                                       York University and Vector Institute                                                              February 2024 – Present, Toronto, Canada

  • Received the Connected Minds CFREF Scholarship, funded by the Canada First Research Excellence Fund.

  • Develop innovative solutions for integrating Large language models to investigate mental health problems. The goal is to design frameworks and algorithms that enable AI models to make fair, transparent, and contextually aware health recommendations

  • Primary Supervisor - Dr. Elham Dolatabadi, Co-supervisor - Dr. Laleh Seyyed-Kalantari, External Collaborator (CAMH) - Dr. Stephanie Ameis (Psychiatrist and Scientist), and External Collaborator (Vector Institute & Dalhousie University) - Dr. Frank Rudzicz.​​​

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Machine Learning Associate
Vector Institute and Kids Help Phone                                                                   May 2024 - Current, Toronto, Canada

  • Collaborate with Vector Institute and Kids Help Phone to implement Large Language models to classify mental health issues in young people.

  • Building technology that can predict the mental health needs of young people to reduce the administrative burden on counselors.

  • Skills: Python, Large Language Models, Llama 3, AWS, Text data preprocessing, and system prompt.

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Research Assistant - Ontario Tech University- Canada                                                                May 2020 - April 2024

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Research Assistant-Ontario Shores Mental Health Institute, Whitby, Canada                                  Jan 2023 - May 2024

  • Led the project Collaboration between Ontario Shores Mental Health Institute and Ontario Tech University titled Leveraging AI to detect, predict, and manage Neuropsychiatric Symptoms (NPS) in People with Dementia (PwD). I cooperated with the hospital team to propose and accept the project by the Research Ethics Board and implement an entire detection system in the dementia unit.

 

Research Assistant- University Health Network and University of Toronto, Canada                       Jan 2022 - June 2023

  • Research Trainee at the KITE Research Institute and IATSL lab at the University of Toronto on the project titled Multimodal Human Activity Recognition from wearable inertial sensors using machine learning. This study investigates the use of features and machine learning to detect people with dementia behavior when agitation and aggressive behavior occur.

  • https://iatsl.org/people/abadawi.html

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Data Scientist - BetterCart Technologies Inc. - Internship - Canada                                                July 2021 - July 2022

  • Code,  debug, and optimize the BetterCart platform, and support, refactor, and enhance existing systems.

       Enhance the data science, analytics, and programming capacity of BetterCart.

  • Build NLP and NER systems to extract grocery store data and create a product-matching algorithm using classification techniques.​

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Instructor Lecturer in Computer Engineering                                                      May 2024 - current, Oshawa, Canada

Ontario Tech University

  • Prepared and delivered lectures on Introduction to Programming using C++ programming language.

  • Introduce a new learning tool named ZyBooks with Canvas to help students engage more during lectures and learn coding skills.

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Teacher Assistant - Ontario Tech University- Canada                                                                  May 2020 - April 2024

  • I delivered tutoring support to students, assisting them with coursework assignments, projects, and exam preparation. I instructed tutorials and lab sessions, held office hours, and evaluated assignments, quizzes, and final projects.

  • Courses: Introduction to Programming ENGR1200, Microprocessor and Computer Architecture ELEE3450, Introduction to Artificial Intelligence SOFE 3720U.​

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Teacher Assistant at Arab Academy for Science and Technology - Egypt                                      Sep 2016 – June 2019

  • Teacher Assistant for 13 different Computer, Electrical, Communication, and Electronics courses.

  • Assessed student assignments to check quality and completeness before submission for grading.

  • Prepare course manuscripts for Elective courses to teach students how to read and write academic research papers.

  • Develop lab content for Python programming language for Introduction to a computer course.

Education

Education

 

Ph.D. in Electrical and Computer Engineering                                                                                 May 2020 - April 2024

Ontario Tech University

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  • Ph.D. candidate in the Electrical and Computer Engineering department.

  • Courses: Topics in Data Mining, Real-Time Data Analysis, Knowledge Discovery and Data Mining, and Data Visualization.

  • Current GPA 4.22/4.3. • Nominated for the best thesis award, GPA 4.22/4.3, and received Ontario Graduate Scholarship (OGS)

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Master of Science: Electronics and Communication Engineering                                                     Sep 2016 – Dec 2018 

Arab Academy For Science And Technology - Egypt

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  • GPA: 3.96/4.0, Excellent with Honor.

  • Thesis: Multimodal Human Activity Recognition from Wearable sensors using Machine learning and a Feature Selection approach.

  • Created a new framework using Machine Learning algorithms to improve the recognition of human activities with an accuracy of 99.8%.

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Bachelor of Science: electronics and communication engineering                                                   Spe 2011 – June 2016

Arab Academy For Science And Technology - Egypt

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  • GPA: 3.95/4.0, Excellent with Honor.

  • Graduation project: PortaCare: IoT-Based Portable-Intensive-Care-Unit.

  • Biomedical Engineering/Health information transactions over mobile and wireless networks. Won national funding from the Information Technology Industry Develop Agency (ITIDA).

Publications

1. BADAWI, A., Elmoghazy, S., Choudhury, S., Elgazzar, K., & Burhan, A. M. (2024). Leveraging self-training and variational autoencoder for agitation detection in people with dementia using wearable sensors. arXiv preprint arXiv:2412.19254.

2. BADAWI, A., Elmoghazy, S., Choudhury, S., Elgazzar, S., Elgazzar, K., & Burhan, A. M. (2024). A novel multimodal system to predict agitation in people with dementia within clinical settings: A proof of concept. arXiv preprint arXiv:2411.08882.

3. Choudhury, S., BADAWI, A., Elgazzar, K., Kumar, S., & Burhan, A. M. (2024). Profile of NPS in neurocognitive disorders: Sex differences, and identifying targets for digital biometrics. Alzheimer's Association International Conference.

4. BADAWI, A., Badr, A., Elmoghazy, S., Elgazzar, S., Elgazzar, K., & Burhan, A. M. (2024). A real-time system for monitoring and managing neuropsychiatric symptoms in dementia patients. Proceedings of the 2024 6th International Conference on Communications, Signal Processing.

5. BADAWI, A., Choudhury, S., Elgazzar, K., & Burhan, A. M. (2023). Artificial intelligence and features investigating to detect neuropsychiatric symptoms in patients with dementia: A pilot study. 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 741-746.

6. Burhan, A. M., Sun, W., Chiu, M., Choudhury, S., BADAWI, A., & Elgazzar, K. (2023). S13: Technology-enabled care for neuropsychiatric symptoms of dementia: Implementation at the point of care. International Psychogeriatrics, 35(S1), 40-40.

7. BADAWI, A., Elgazzar, K., Ye, B., Newman, K., Mihailidis, A., Iaboni, A., & Khan, S. S. (2023). Investigating multimodal sensor features importance to detect agitation in people with dementia. 2023 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE).

8. BADAWI, A., & Elgazzar, K. (2021). Detecting coronavirus from chest X-rays using transfer learning. Covid, 1(1), 403-415.

9. BADAWI, A. A., Al-Kabbany, A., & Shaban, H. A. (2020). Sensor type, axis, and position‐based fusion and feature selection for multimodal human daily activity recognition in wearable body sensor networks. Journal of Healthcare Engineering, 2020(1), 7914649.

10. BADAWI, A. A., Al-Kabbany, A., & Shaban, H. (2018). Multimodal human activity recognition from wearable inertial sensors using machine learning. 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES).

Volunteer

Volunteer Experience

1-  Reviewer- The Journal of Supercomputing (Springer), IEEE GCAIoT 2023, IWCMC 2022, ICCSPA 2022.

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2- Volunteer in Conference- Volunteered in the Machine Learning for Healthcare 2024 conference and IEEE Smart Mobility 2024 conferences.

 

3-Former IEEE-HKN Mu Beta chapter President, Arab Academy for Science and Technology, Alexandria, Egypt. 

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  • The president and founder of the IEEE Eta Kappa Nu (IEEE-HKN) - Mu Beta Chapter Arab Academy for Science and Technology College, the first chapter in Africa and Egypt.

  • Won the Outstanding Chapter Award for 2019

  • The chapter's main aim is to help and support students pursuing their first academic degree in university, faculty members, and professional members.

  • Facebook page: https://www.facebook.com/HKN.Mu.Beta

 

4- Former Team Leader in AIESEC youth organization, Alexandria, Egypt.

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  • Talent Management team leader to Guide members to set and fulfill their goals from a personal and professional perspective.

  • Member at Outing Global Community Development Program.

contact

Contact Information

Toronto, Canada

E-mail: abeer.badawi@ontariotechu.ca 

  Tel. +1 4379713670

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©2021 by Abeer Badawi.

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