Co-Lead of Computational Modeling
University of British Columbia
Muhammad Abdul-Mageed’s research focuses on deep representation learning and natural language socio-pragmatics, with two main goals: (1) development of `social’ machines for improved human health, safer social networking, and reduced information overload; and (2) use of machine learning as a vehicle for making discoveries with and about human language. Examples of Muhammad’s recent work include development of spatial and linguistically-motivated large-scale language models for natural language processing, decoding imagined speech from brain signal, neural detection of misinformation and machine-generated text, multilingual and latent variable neural machine translation, and billion-scale investigation of human communication during COVID-19. As a part of the grant Muhammad is excited about making discoveries about how the human brain encodes language in its different forms and how language learning happens under diverse sets of conditions.