Signal Analysis & Machine Intelligence
The Signal Analysis and Machine Intelligence (SAMI) group at the Electrical and Computer Engineering Department, National University of Singapore is actively working on a broad range of research topics in artificial intelligence, that include medical image processing, human language technology, computer and human vision, and machine learning.
SAMI is home to world-class faculty and researchers working on exciting real-world research problems with industry and research groups around the world. It is known for its long standing scientific leadership in computer vision, brain imaging analysis, speech recognition and synthesis, and human-robot interaction.
SAMI group fosters use-inspired research. The ability to model, annotate, search, organize visual and verbal knowledge has the potential to make significant impact in a variety of fields including medicine, manufacturing, education, entertainment, and defence. A key goal is to develop engineering systems that can “see”, “hear” and “interact” intelligently with the world around them.
Research Focus
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Computational and Cognitive Neuroscience:
The Computational and Cognitive Neuroscience group exploits computational techniques from machine learning, signal processing and statistics to advance our understanding of the brains of humans and non-human primates. Current focus includes the development of machine learning algorithms to automatically generate scientific discoveries from large-scale magnetic resonance imaging data sets, as well as population decoding techniques for analyzing large-scale electrophysiological data recorded in awake, behaving animals performing working memory and spatial navigation tasks.
- Computer Vision and Machine Learning:
The Computer Vision and Machine Learning group has focused on the most original research and technologies at the edges for computer vision, machine learning and their applications in real life. The group undertakes research projects from both industry and national research programs, that include fundamental machine learning and deep learning algorithms, cutting-edge face/human and image/video analytics technologies, and intelligent search and recommendation systems. The group delivered top performing systems in international benchmarking, such as ILSVRC2017 for image localization and MS-Celeb-1M for large-scale face recognition.
People
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Robby Tantowi TAN E4-05-22 +65 6601 5250 Computer Vision and Deep Learning |
YEO Boon Thye, Thomas E2-03-26 +65 6516 1110 Development of machine learning algorithms and statistical models for the large-scale analysis of high-dimensional brain imaging data |
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ZHOU Zhiying, Steven E2-02-03 +65 6516 3754 Computer and machine vision Mixed Reality / Augmented Reality Multimodal Human Computer Interface Computer-Human Interaction Interactive and digital media |
CHEN, Tsuhan +65 6601 7308 |
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Wang Xinchao E4-04-14 +65 6601 6396 |
Mike Z. Shou E4-04-15 +65 6601 6252 |
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Zhou Juan, Helen +65 6601 4918 Computer Vision, and Deep Learning |
