Director, Center for Multimodal Big Data Science and Healthcare
Director, Center for Bio-image Informatics
Department of Electrical and Computer Engineering
University of California
Santa Barbara, CA 93106-9560
- Ph.D. (1991), Signal & Image Processing Institute, EE-Systems, USC.
- M. E. (1987), Systems Science and Automation, Indian Institute of Science, Bangalore, India.
- B. E. (1985), Electronics Engineering, Bangalore University, Bangalore, India.
Manjunath directs the Center for Multimodal Big Data Science and Heathcare. He has published over 300 peer-reviewed articles in various journals and peer reviewed conferences and his publications have been cited extensively. He is an inventor on 24 Patents and co-edited the first book on the ISO/MPEG-7 multimedia content representation standard. He directed the NSF/ITR supported center on Bio-Image Informatics. His team is developing the open-source BisQue image informatics platform that helps users manage, annotate, analyze and share their multimodal images in a scalable manner with a focus on reproducible science.
Past: Director, Interactive Digital Multimedia (IGERT program); ECE Department Vice-Chair and Director, Undergraduate EE Program; Founding faculty, Media Arts and Technology Program.
Links to: Publications, Grants and Contracts (Last 5 Years)
|Vision Research Lab|
Harold Frank Hall (aka Engineering I)
(805) 893 5682
Teaching (Recent courses)
Spring 2019. ECE 595, 596, 196. Selected topics in vision, learning and applications.
Winter 2019. ECE 194. This is a second iteration of the deep learning course. Introduction to Deep Learning (Senior elective covering basics of neural networks (perceptrons, multi-layer networks, back propagation learning); deep learning architectures and applications to NLP, computer vision.
Fall 2018. ECE 178, Introduction to Image Processing. Open to EE and CE majors, and other engineering majors with instructor permission. Basics of image processing, including image transforms, image enhancement and image/video compression.
Spring 2018. ECE 194. Introduction to Deep Learning. open to UG/graduate students in engineering and sciences. Topics include basics of neural networks (perceptrons, multi-layer networks, back propagation learning); deep learning architectures and applications to NLP, computer vision.
Winter 2018, ECE/COMPSC181B, Introduction to Computer Vision (undergraduate). This introductory course covers multiview geometry, edge detection and feature extraction, object recognition.
Fall 2017, ECE 278A, Topics in Image Processing (graduate)
Research Interests: Image/video analysis, including detection, segmentation and classification, weakly supervised detection, activity recognition; multi-modal camera networks. Bisque image informatics open-source project.
Current students and Graduates