Hina Tabassum
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About
Hina Tabassum is an Assistant Professor at York University in Canada. Her research focuses on optimizing communication networks, with recent articles exploring topics such as resource allocation in cell-free networks, joint optimization of vehicular communication, and deep learning frameworks for wireless networks. Her work also includes contributions to self-supervised learning for Wi-Fi sensing and advancements in 6G wireless communication technologies.
Positions (1)
Hina Tabassum
York University
York University’s Lassonde School of Engineering is recruiting a Postdoctoral Fellow / Research Associate for an interdisciplinary project at the intersection of Applied AI , Foundation Engineering , Civil Engineering , Electrical and Computer Engineering , and Geotechnical Engineering . The project is jointly supervised by Prof. Rashid Bashir and Prof. Hina Tabassum and is funded by the Ontario Ministry of Transportation (MTO) and an NSERC Alliance Grant . The research focuses on building an AI-driven pipeline to extract critical geotechnical information from unstructured PDF Foundation Investigation Reports using OCR , NLP , and deep learning . The successful candidate will also develop machine-learning models to predict design parameters such as bearing capacity and settlement behavior . Applicants should hold a Ph.D. in Computer Science , Electrical and Computer Engineering , Civil Engineering (with a strong computational focus), Data Science , or a closely related field. Strong experience in machine learning and/or artificial intelligence is required, along with proficiency in Python , R , MATLAB , or equivalent tools. Familiarity with geotechnical concepts such as soil mechanics and foundation design is expected, and a strong publication record in AI/ML engineering applications is preferred. Experience with NLP and OCR is an asset. The post specifically notes that the candidate should currently be located within Canada . The anticipated start date is August 15, 2026 . To apply, send a CV, cover letter, research statement, and 2–3 academic references to both supervisors by email. This is a strong fit for candidates interested in computer science , civil engineering , geotechnical engineering , AI/ML , and document intelligence for infrastructure applications.
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Collaborators (6)
Jeroen Famaey
Prof. at University of Antwerp
University of Antwerp
Rafael Berkvens
Assistant Professor
University of Antwerp
Ping Wang
Associate Professor
York University
Navid Hasanzadeh
University of Toronto
OMER WAQAR
Assistant Professor
University of the Fraser Valley
Hong-Chuan Yang
University of Victoria
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