Danielle Manley - Director of Carleton University’s School of Nursing & Majid Komeili - Director of the Intelligent Machines Lab at Carleton University Podcast Por  arte de portada

Danielle Manley - Director of Carleton University’s School of Nursing & Majid Komeili - Director of the Intelligent Machines Lab at Carleton University

Danielle Manley - Director of Carleton University’s School of Nursing & Majid Komeili - Director of the Intelligent Machines Lab at Carleton University

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Danielle Manley, Director, School of Nursing, Carleton University

Danielle Manley is the Director of Carleton University’s School of Nursing and a Registered Nurse specializing in healthcare innovation, curriculum development and AI in medicine and education. She has led efforts to optimize electronic healthcare charting systems and align nursing scope of practice with regulatory standards.

Her research focuses on AI’s role in reducing administrative burdens, supporting clinician and patient autonomy and improving medical education. She is actively involved in developing nursing curricula that bridge the theory-practice gap and address healthcare provider burnout.

Manley is a recognized speaker on AI in healthcare, serving as a plenary speaker at the SIMposium 2025 and joining Madison Industries Healthcare Townhall on Innovations in the International Medical Landscape. She led the creation of Ontario’s first new standalone university nursing school in over 20 years, driving innovation in nursing education and practice.


Majid Komeili, Director, Intelligent Machines Lab (iML), Carleton University

Majid Komeili is an Associate Professor at the School of Computer Science, a faculty member at the Institute for Data Science, a faculty affiliate at the Accessibility Institute, and the Director of the Intelligent Machines Lab (iML) at Carleton University. He conducts fundamental and applied research in machine learning and related areas in natural language processing and computer vision with a focus on AI explainability and transparency.

Komeili conducts interdisciplinary research on AI-driven solutions for real-world issues, including using machine learning to predict an individual’s risk of chronic homelessness to support early and effective intervention, developing AI-assisted assessment of disability and functional limitations in post-secondary settings, and exploring generative AI for communicating graphical information to persons with vision impairment—all with the goal of building intelligent systems that create social impact.

Before joining Carleton University, Komeili was a postdoctoral fellow at the University of Toronto working jointly with Toronto Rehabilitation Institute and the Vector Institute, fostering innovation for public good.

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