MIT Director, MIT-IBM Watson AI Lab; Director of Strategic Industry Engagement, MIT Schwarzman College of Computing
Who they work with
Aude Oliva, PhD is the MIT director in the MIT-IBM Watson AI Lab and director of strategic industry engagement in the 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 MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), 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 a MS and PhD in cognitive science from the Institut National Polytechnique de Grenoble, France.
- Andonian, A., Fosco, C, Monfort, M., Lee, A., Feris, R., Vondrick, C., & Oliva, A. (2020). We Have So Much In Common: Modeling Semantic Relational Set Abstractions in Videos. Proceedings of the 16th European Conference on Computer Vision (ECCV).
- Newman, A., Fosco, C., Casser, V., Lee, A., McNamara, B., & Oliva, A. (2020). Multimodal Memorability: Modeling Effects of Semantics and Decay on Video Memorability. Proceedings of the 16th European Conference on Computer Vision (ECCV).
- Fosco, C., Newman, A., Sukhum, P., Zhang, Y., Zhao, N., Oliva, A., & Bylinskii, Z. (2020). How much time do you have? Modeling multi-duration saliency. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
- Mohsenzadeh, Y., Mullin, C., Lahner, B., & Oliva, A. (2020). Emergence of Visual Center-Periphery Spatial Organization in Deep Neural Networks. Scientific Reports 10:4638.
- Monfort, M., Andonian, A., Zhou, B., Ramakrishnan, K., Adel Bargal, S., Yan, T., Brown, L., Fan, Q., Gutfreund, D., Vondrick, C., & Oliva, A. (2020). Moments in Time dataset: one million videos for event understanding. IEEE Pattern Analysis and Machine Intelligence (PAMI), 42(2), 502-508.
- Goetschalckx, L., Andonian, A., Oliva, A., & Isola, P. (2019). GANalyze: Towards Visual Definition of Cognitive Image Properties. IEEE International Conference on Computer Vision (pp. 5744-5753).
- Xiao, T., Fan, Q., Gutfreund, D., Monfort, M., Oliva, A., Zhou, B. (2019). Reasoning About Human-Object Interactions Through Dual Attention Networks. IEEE International Conference on Computer Vision (pp. 3919-3928).
- October 13, 2021: MIT News, Thriving Stars: An initiative to improve gender representation in electrical engineering and computer science.
- August 31, 2020: MIT News, Toward a machine learning model that can reason about everyday actions.
- November 1, 2019: MIT News, What makes an image memorable? Ask a computer.
- September 13, 2018: MIT News, Helping computers fill in the gaps between video frames.
- June 29, 2017: MIT News, Peering into neural networks.