Sathyanarayanan N. Aakur, Ph.D.
Event perception, Computer Vision, Abductive reasoning for problem solving, Genome/Metagenome analysis
|Degree:||PhD, Computer Science|
|Seeking Collaborators with Skill Sets:||
|Neuroscience Research Interests:||My research is currently focused on building computer vision systems for open-world understanding i.e., without the need for annotated training data. I take inspiration from cognitive theories of event perception to build generic event understanding models in computer vision using deep learning and neuro-symbolic reasoning. I am interested in extending this research into building active vision systems that build upon theories of sensori-motor control from neuroscience and cognitive science. I also dabble in metagenome analysis with deep learning to understand disease evolution and diagnosis.|
|Funding in the Last Three Years:||
NSF CISE (RI), NASA
"A perceptual prediction framework for self supervised event segmentation." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019.
"Action Localization through Continual Predictive Learning." Proceedings of the IEEE/CVF European Conference on Computer Vision. 2020.
"Unsupervised Gaze Prediction in Egocentric Videos by Energy-based Surprise Modeling." arXiv preprint arXiv:2001.11580 (2020).
"Genome Sequence Classification for Animal Diagnostics with Graph Representations and Deep Neural Networks." arXiv preprint arXiv:2007.12791 (2020).