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External Projects

	Multimedia Medical Conceptual Web for Intelligent Information Access SERC - ASTAR – Science & Engineering Research Council, Agency for Science, Technology and Research – Singapore Partners:* - National University Hospital (NUH, Singapore), - National Healthcare Group (NHG, Singapore) and Singapore General Hospital (SGH, Singapore). MmedWeb project proposes to develop a framework for the semantic structuring and organization of multimedia medical information, including medical images and medical reportsProposed.
Onco-Media	Ontology and COntext related MEdical image Distributed Intelligent Access ICT ASIA Project (Ministère des Affaires Étrangères– MAE, France) Partners: - UNIGE (University Hospitals of Geneva, Switzerland), - CREATIS (Lyon, France), - LIRIS (Lyon, France), - NTU Taiwan, - CASIA (Institute of Automation, Chinese Academy of Sciences, Beijing, China), - Ateneo de Manila University (Philippines), - National Center for Geriatrics and Gerontology (NCGG, Japan), - LIP6 (Laboratory of Computer Sciences, Paris 6, France). The aim of ONCO-MEDIA project is to deploy a medical image semantic content-based application on a large scale grid tested, by taking into account the context of the user and of the navigation / query and by matching semantic visual concepts extracted from the medical image with those (textual) extracted from the associated medical reports
	Mobile Search and Annotation using Images in Context ICT ASIA Project (Ministère des Affaires Étrangères – MAE, France) Partners: - NII (National Institute of Informatics, Tokyo, Japan), - NTU (Dept of Computer Science and Information Engineering National Taiwan University), - MICA (International Research Center MICA, Hanoi, Vietnam), - CLIPS-IMAG (Communication Langagiere et Interaction Personne Systeme, Grenoble France), - LIRIS (Laboratoire d'InfoRmatique en Image et Systèmes d'information, Lyon, France). The MoSAIC project will develop a novel mobile search and annotation framework using images in context. Camera phones are both communication and image capturing devices. However, unconstrained image recognition is an open research problem. Contextual information such as geospatial cues would help to narrow the search space, return answers with higher relevancy, and provide meaningful annotations to the query logs.
GRASP-IT	Merlion programme, French Embassy (Aug. 2007- Jul. 2010)
Remove Visualization of Large Collections of 3D Data	Merlion programme, French Embassy (Aug. 2008 - Jul. 2010)
mCity: Street Scene Indexing and Retrieval	Merlion programme, French Embassy (June. 2010 - June. 2013)
AMUPADH	Activity Monitoring and UI Plasticity for supporting Ageing with Mild Dementia at Home (AMUPADH) - A*STAR SERC (2 years - May 2010 – April 2012)

Internal Projects

The Cognitive Microscope	The Cognitive Microscope The cognitive microscope aims at developing a cognition-driven visual explorer for histopathology. The clinical goal is a realiable breast cancer grading from histopathological images. Partners: - TRIBVN (France), - National University Hospital (NUH, Singapore).
Snap2Tell	This project studies the role of small mobile devices and picture to access information. In this project, we focus on scene identification based on image examples with geospatial cues. This is a challenging problem as image objects are usually multi-scaled, ill-posed, occluded and cluttered, captured with different lighting conditions, focus, exposure and viewing perspectives.
A*STAR CCO Grant (Dec 2009-Nov.2012)	An Intelligent Vision System for Quantitative Microscopy in Neural Stem Cells Progenitor Growth and Differentiation A*STAR CCO (Cross Council Office) Summary : This project combines neural stem cell biology, microscopy, image processing and machine learning research to realize an integrated intelligent vision system for systematic studies of neural stem cells. Images generated in the biological laboratories are processed using automated algorithms to extract special image features that will then be analyzed by machine learning techniques to understand the content and context of the image data. Multi-variable statistical analysis and data modelling can then be used to summarize and extract important information to generate new biological hypothesis. These new biological hypothesis will then be tested again in the biological laboratories.
A*STAR JCO	An Intelligent Vision System for Quantitative Microscopy in Neural Stem Cells Progenitor Growth and Differentiation A*STAR JCO (Joint Council Office) (3 years - Jan. 2010 – Dec. 2012)