and Computer Science
University of Michigan
Jason J. Corso
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VQA action detection action prediction action segmentation active clustering activity recognition artificial intelligence attribute augmented reality autonomous driving belief propagation bioinformatics biomarkers biometrics braintumor cognitive systems computational finance computer forensics computer graphics computer vision computer-aided diagnosis control cosegmentation data mining deep learning deep reinforcement learning deformable dictionary transfer digitial humanities document imaging domain adaptation dynamic linear models endoscopy evaluation event recognition facade detection face detection face recognition feature extraction frame interpolation fusion gesture recognition gpu grammar graph cuts graph-based graphical models haptics hierarchical higher-order human pose estimation human-computer interaction human-in-the-loop hybrid intelligence image captioning image denoising image processing image retrieval image understanding inference information fusion inpainting language grounding localization lung imaging machine learning mapping max-margin medical imaging metric learning mobile manipulation mobile robotics mosaicking motion estimation mrf multimedia natural language navigation neuroimaging object detection object grounding object-object interaction ontology particle filters pretraining probabilistic ontology protein structure prediction random forest reconstruction robotics segmentation semantic segmentation semi-supervised single-view depth estimation sketch generation slam spectral clustering spine imaging stereo streaming supervoxel surgical robotics tomographic reconstruction tracking video inpainting video object segmentation video prediction video saliency video segmentation video summarization video to text video understanding viewpoint estimation vision and language vision-based control visual psychophysics visual servo control volume rendering voxel maps weak supervision
Dr. Jason J. Corso is currently a Professor of Electrical Engineering and Computer Science at the University of Michigan. He received his Ph.D. in Computer Science at The Johns Hopkins University in 2005. He is a recipient of the NSF CAREER award (2009), ARO Young Investigator award (2010), Google Faculty Research Award (2015) and on the DARPA CSSG. He is also the Co-Founder and CEO of Voxel51, a computer vision tech startup that is building the state of the art platform for video and image based applications.
His main research thrust is high-level computer vision and its relationship to human language, robotics and data science. He primarily focuses on problems in video understanding such as video segmentation, activity recognition, and video-to-text. From biomedicine to recreational video, imaging data is ubiquitous. Yet, imaging scientists and intelligence analysts are without an adequate language and set of tools to fully tap the information-rich image and video. He works to provide such a language; specifically, he primarily studies the coupled problems of segmentation and recognition from a Bayesian perspective emphasizing the role of statistical models in efficient visual inference. His long-term goal is a comprehensive and robust methodology of automatically mining, quantifying, and generalizing information in large sets of projective and volumetric images and video.