Aude Oliva is the director of strategic industry engagement in the Schwarzman College of Computing, the MIT director of MIT-IBM Watson AI Lab, and senior research scientist in the Computer Science and Artificial Intelligence Lab (CSAIL) at the Massachusetts Institute of Technology.
In her role as director of strategic industry engagement, Oliva develops and implements relationships between the College and corporate collaborators. The goal of these enterprising academic-industry collaborations is to develop and translate novel computing and artificial intelligence research into tools for real-world impact. For this, she interfaces with those interested in large-scale, multi-faceted engagements comprising research, student support, community building, and public interaction activities at MIT. Holding stewardship roles in the MIT AI Hardware Program, and the MIT Department of Electrical Engineering & Computer Science (EECS) Alliance, Oliva constructs and facilitates instrumental pipelines that, respectively, deliver AI hardware and software with significantly enhanced energy efficiency systems, and she promotes career opportunities and visibility for EECS students and participating companies. As head of the MIT-Amazon Science Hub, a collaboration between MIT and Amazon, she extends this expertise to the realm of robotics and AI to research and develop new tools for the future of industry.
Oliva earned a PhD and MSc in cognitive science from the Institut National Polytechnique of Grenoble, France, in addition to a MSc in experimental psychology from the Université Grenoble Alpes, France. She has her French baccalaureate in physics and mathematics and a BSc in psychology (minor in Philosophy). Oliva’s interdisciplinary research and publications span human perception/cognition, computer vision (visual AI), and cognitive neuroscience, focusing on their intersection. Her work in computational perception and cognition builds on the synergy between human and machine recognition, and how it applies to solving high-level recognition problems like understanding scenes and events, perceiving space, modeling attention, eye movements and memory, as well as predicting subjective properties of images (like memorability). Her research integrates knowledge and tools from computer vision, machine learning, deep neural networks as well as human perception, cognition and neuro-imaging (fMRI, MEG).
She is the recipient of several honors, including a National Science Foundation (NSF) CAREER Award in computational neuroscience, a Guggenheim fellowship in computer science, and a 2016 Vannevar Bush Faculty Fellowship in cognitive neuroscience. Oliva is an elected fellow of the Association for Psychological Science. 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 and is a current member of the scientific advisory board for the Allen Institute for Artificial Intelligence. Oliva has served as editor and on the board on cognitive science journals, is listed on five patents, and has co-authored over 200 book chapters and reviews, journal publications and conference proceedings.