Scholar
Leila Wehbe
Google Scholar ID: YezyUawAAAAJ
Associate Professor, Carnegie Mellon University
Citations & Impact
Citations
1,827
H-index
20
i10-index
27
Publications
20
Co-authors
11
list available
Contact
Publications
Resume (English only)
Academic Achievements
- NIH R21 award for modeling depression in developmental data using machine learning
- NSF CAREER award on 'Uncovering the brain circuitry of language and its interaction with other modalities'
- Human Frontier Science Program award on 'Understanding the neural basis of early language development'
- NIH R01 (CRCNS) award on 'Discovering Principles of Language Processing in the Brain using Neurocomputational Models'
- Google Faculty Research Award
- Research on food featured in NewScientist
- Tutorial Chair for UAI 2022
- Program Committee Member for Cognitive Computational Neuroscience (CCN) 2022
- Co-organized ICLR workshop 'How Can Findings About The Brain Improve AI Systems?'
- Co-organized CVPR workshop 'Minds vs. Machines: How far are we from the common sense of a toddler?'
- Co-organized workshop on 'Context and Compositionality in Biological and Artificial Neural Systems'
- Interviewed for the book 'Artificial Intelligence: Teaching Machines to Think Like People'
Background
- Associate Professor in the Machine Learning Department and the Neuroscience Institute at Carnegie Mellon University
- Affiliated with the Department of Psychology and the Computational Biology Department
- Research focuses on using fMRI and MEG to investigate how the brain represents complex meaning in everyday life
- Develops machine learning methods to address challenges in neuroimaging: high dimensionality, noise, limited data, and inter-subject anatomical variability
- Explores the neural basis of language compositionality by integrating computational language models with brain data
