The One About AI x Healthcare (Round III)
More information to come soon - keep a lookout!
More About the Sharings
Yan Chun (Data Scientist, Synapxe) will share practical insights from developing Synseh an AI system for tongue diagnosis, a key diagnostic method in Traditional Chinese Medicine (TCM). She will also discuss data collection, feature extraction and the importance of domain collaboration. (Technical Level: 100-200)
RNA medicine holds immense promise for treating a vast array of diseases as demonstrated by the success of mRNA vaccines against COVID-19. However, designing effective RNA therapies remains a complex challenge. To overcome this hurdle Alvin's team has developed COMET an AI-powered tool capable of rapidly designing novel RNA nanomedicines. COMET is based on deep learning and streamlines the design process by virtually testing tens of millions of potential formulations, eliminating the need for costly and time-consuming experiments. This approach enables the creation of RNA therapies that are not only more effective and specific but also exhibit enhanced stability. (Technical Level: 100 -200)
More About the Speakers
Ong Yan Chun is a data scientist at Synapxe, where she develops AI-driven solutions to support healthcare delivery and improve patient outcomes. With a background in both analytics and healthcare, Yan Chun is passionate about bridging the gap between data science innovation and practical, impactful deployment in public health settings. Her recent projects include building AI-assisted chronic disease prediction tools, applying large language models to improve manual workflows, and developing innovative AI tools in the TCM domain.
Dr. Alvin Chan is an Assistant Professor at Nanyang Technological University, jointly appointed in the College of Computing and Data Science and the Lee Kong Chian School of Medicine. He builds AI systems to accelerate therapeutic discovery and precision medicine, with a focus on RNA therapeutics and targeted drug delivery. His research bridges deep learning and biomedical engineering to accelerate medical innovation. Prior to NTU, Alvin was a postdoctoral fellow at MIT, where he developed AI frameworks to enhance the accessibility and efficacy of RNA nanomedicine. His work has been featured in Nature Nanotechnology, ICLR, and NeurIPS, spanning foundational advances in generative modeling to real-world applications in drug design. With a background in both bioengineering and computer science, Alvin is committed to translating machine learning into clinically meaningful impact.
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