Chuan-Sheng FooView profile
Researcher
Chuan-Sheng Foo serves as the Deputy Head of the Machine Intelligence Department at the Institute for Infocomm Research (I2R), part of Singapore's Agency for Science, Technology and Research (A*STAR). His research focuses on data-efficient deep learning approaches for applications in healthcare and manufacturing, where large annotated datasets are difficult to obtain due to the need for expert labeling and associated costs. Foo earned his academic credentials from Stanford University with a BS ('08), MS ('12), and PhD ('17) in Computer Science. During his doctoral studies, he collaborated with prominent researchers including Professors Anshul Kundaje, Daphne Koller, Andrew Ng, and Serafim Batzoglou on machine learning applications in biology. Notably, he took a year away from his PhD to develop software for clinically validated genetic tests at Counsyl, where he worked on variant calling and LIMS integration. Foo's research spans multiple AI domains with a consistent focus on developing machine learning methods that require minimal labeled data. His work encompasses semi-supervised learning, generative models (particularly GANs), computer vision, medical imaging, and computational biology. He has made significant contributions across theoretical foundations and practical applications, especially in healthcare contexts where expert annotation is costly. His publication record shows an evolution from foundational machine learning algorithms to increasingly applied research with strong healthcare connections. Early work focused on hyperparameter optimization and RNA structure analysis, while recent publications address computer vision challenges, GAN training improvements, and medical imaging applications. A unifying theme across his career is the development of techniques that maximize performance with limited labeled data. Foo has received numerous prestigious awards throughout his academic journey: Computing Research Association Outstanding Undergraduate Researcher Award (2008) UCSD Data Mining Contest: 1st, 2nd (2006), 3rd (2007), 2nd (2008) Top 200 ranking on the Putnam Mathematics Competition (2005) President's Award for Academic Achievement in the Freshman Year (2006) Best Paper Award at the 16th International Conference on Genome Informatics (2005) A*STAR National Science Scholarship (2002) Bronze medal at the 33rd International Physics Olympiad (2002) As Deputy Head of Department at I2R, Foo leads a research group focused on data-efficient deep learning. His collaborative approach is evident in numerous co-authored publications across multiple domains, particularly in applying machine learning to biological and medical challenges. His work at A*STAR likely involves significant research funding supporting his team's development of practical AI solutions for real-world problems where data annotation presents significant barriers.
