Canceled: CBMM Brains, Minds, and Machines Seminar Series: Mapping Responses in the Human Brain Through Space and Time
Description
Due to unforeseen circumstances, we have had to cancel today’s talk.
We will reschedule this talk in the near future.
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Abstract: The human brain is a time machine; We are constantly remembering our past, and projecting ourselves into the future. Capturing the brain’s response as these moments unfold could yield valuable insights into both how the brain works and how to better design human-centered AI systems. In this talk, I will present our research on the human brain spatiotemporal dynamics of perceived or imagined events, using a combination of MEG (magneto-encephalography) and fMRI (functional magnetic resonance imaging) methods. The fusion of both methods could lead to the development of biomarkers to aid clinicians in diagnosing disease, identifying cognitive impairments, finding ways to maintain or augment perception and cognition in healthy brains, and developing new brain-inspired machine-learning architectures.
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The seminar talk will be hosted remotely via Zoom.
Zoom link: https://mit.zoom.us/j/98465525998?pwd=UHRVQStlbXNDc0VEQ29MTldFRmlFQT09
Passcode: 588132
Speaker Bio
Prof. Aude Oliva, Senior Research Scientist, CSAIL; MIT Director MIT-IBM Watson AI Lab; Director MIT Quest Corporate; MIT
Speaker Biography: Aude Oliva, Ph.D. is the MIT director of the MIT–IBM Watson AI Lab and director of MIT Quest Corporate, MIT Schwarzman College of Computing, leading collaborations with industry to translate natural and artificial intelligence research into tools for the wider world. She is also a senior research scientist at the Computer Science and Artificial Intelligence Laboratory where she heads the Computational Perception and Cognition group. Oliva has received an NSF Career Award in computational neuroscience, a Guggenheim fellowship in computer science and a Vannevar Bush Faculty Fellowship in cognitive neuroscience. She has served as an expert to the NSF Directorate of Computer and Information Science and Engineering on the topic of human and artificial intelligence. She is currently a member of the scientific advisory board for the Allen Institute for Artificial Intelligence. Her research is cross-disciplinary, spanning human perception and cognition, computer vision, and cognitive neuroscience, and focuses on research questions at the intersection of all three domains. She earned an MS and Ph.D. in cognitive science from the Institut National Polytechnique de Grenoble, France.