More details about the winners and their research as follows:
Molecular and Vascular Medicine
Researcher: Assistant Professor Christine Cheung (Nanyang Assistant Professor, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore; Joint Investigator, Institute of Molecular and Cell Biology (IMCB), A*STAR)
Research Content: Nanyang Assistant Professor Christine Cheung, 34 years old, is the new recipient of the 2018 Life Sciences Fellowship for her research on the genetic basis of vascular ageing. The crux of many ailments like stroke and dementia lies in blood vessels and understanding how blood vessels age forms the impetus for her research. She leads a team to invent novel methods of converting human stem cells into vascular cells, including those found in the brain or heart. These organ-specific vascular cells enables the study of why certain genetic disorders preferentially inflict vascular beds of specific organs, and also opens the door to drug screening and regenerative medicine through the development of personalized blood vessels.
“We are finding means to restore blood vessel health before adverse outcomes of diseases occur with the goal of working towards preventive medicine.”
Quantum Control of Ultracold Molecules
Researcher: Assistant Professor Loh Huanqian (President's Assistant Professor, Department of Physics, NUS; Principal Investigator, Centre for Quantum Technologies, NUS)
Research Content: With a research focus on the quantum control of ultracold molecules at the single-molecule, single- quantum-state level, NUS Assistant Professor Loh Huanqian, 35 years old, is awarded the 2018 Physical and Engineering Science fellowship. Advanced materials like superconductors revolutionize the electronics industry and renewable energy sector, but their microscopic-scale behavior remains poorly understood due to its strongly interacting quantum particles with dynamics that are impossible to calculate even with powerful computers. Assistant Professor Loh’s research directly recreates models of these materials from the bottom-up using ultracold molecules that comprise of quantum properties that can be precisely controlled by lasers and laboratory-applied fields. She have recently demonstrated record-long coherence times in these molecules, paving the way for using these molecules as quantum simulators of advanced materials.
“The idea that you can precisely control every quantum property of an atom or molecule is fascinating and powerful. I hope to use this control to create new materials that could lead to better electronics and faster computers.”
This year’s winning Fellows were selected by an esteemed jury, led by Jury President, Professor Christina Chai, Head of Department, Department of Pharmacy, NUS.The other members are:
• Prof Leo Tan, Chairman, Science Sub-Commission Singapore National Commission for UNESCO & Director (Special Projects), Faculty of Science, NUS
• Assoc Professor Gan Chee Lip, Director, Renaissance Engineering Programme & Director, Temasek Laboratories, NTU
• Assoc Professor Low Hong Yee, Engineering Product Development, SUTD
• Dr Lisa Ng, Senior Principal Investigator, Laboratory of Microbial Immunity, Singapore Immunology Network, A*STAR
• Dr Shawn Lim, Director, Advance Research Labs, L'Oréal Research & Innovation Singapore
Runners Up: The 2018 Life Science Finalists (not in order of merit)
a. Name/Designation: Dr Ng Shi Yan, Principal Investigator, Institute of Molecular and Cell Biology (IMCB), A*STAR; Assistant Professor, Department of Physiology, National University of Singapore
Research Topic: Stem Cells and Neurotherapeutics
Research Summary: Human induced pluripotent stem cells (iPSCs) are valuable tools for dissecting disease mechanisms, and hold great promise for regenerative medicine. In Dr Ng’s laboratory, she used iPSCs derived from patients who suffer from neurodegeneration, and to understand identify why these patients are particularly vulnerable compared to those affected neuronal types. Her goal is to develop an effective treatment for Amyotrophic Lateral Sclerosis (ALS), an age-onset motor neuron disease.
b. Name/Designation: Dr Sarah Ng, Head, Genome Innovation Lab, Genome Institute of Singapore (GIS), A*STAR
Research topic: Longitudinal analysis of circulating tumour DNA to identify novel treatment windows for cancer
Research summary: Dr Ng’s research analyses serially collected cancer patient plasma samples, in order to infer tumour dynamics over time that correlate with clinical events. Using her developed sequencing methods for the accurate detection of circulating tumour DNA using unique molecular identifiers, the real-time surveillance of patient tumours will enable her to find new treatment windows for intervention, with the goal of forestalling cancer progression and advanced disease.
Runners Up: The 2018 Physical & Engineering Science Finalists (in no order of merit)
a. Name/Designation: Dr Yang Le, Research Scientist, Institute of Materials Research and Engineering (IMRE), A*STAR
Research topic: Luminescent Materials: Towards A ‘Brighter’ Future.
Research summary: Smart living such as virtual reality, intelligent wearable sensors and gadgets require luminescence – in display, lighting or transmission. Dr Yang’s research interests aim to thoroughly exploit the photo physical mechanisms in materials, willfully control photon emission, and purposefully design devices towards sensible applications. Her most recent achievement on harnessing a new mechanism in a novel class of materials led to record-efficiency organic LEDs, bringing printable display technology to new heights. Her current research priorities cover “Beating the blues” in organic electroluminescence and pushing the envelope in visible light communications.
b. Name/Designation: Dr Pavitra Krishnaswamy, Head, Deep Learning for Healthcare Programme, Institute for Infocomm Research (I2R), A*STAR
Research topic: Knowledge-Augmented Machine Learning for Healthcare Applications
Research summary: Artificial intelligence has the potential to reduce costs and improve outcomes in healthcare. This requires the integration of machine learning approaches that can detect nuanced patterns in massive clinical datasets, with domain knowledge that can enable non-apparent and actionable insights. Dr Krishnaswamy’s research advances hybrid approaches that integrate statistical learning and inference with domain knowledge for improved efficiency, accuracy, interpretability in medical imaging and clinical decision support applications. Her goal is to drive a future where AI can seamlessly leverage clinical data to generate and translate predictions to explainable insights and recommendations for end-user adoption.