A Perspective that proposes a step-by-step method for translating AI-discovered patterns into testable hypotheses for research and engineering.

Joining NUS CDE under the Returning Singaporean Scientists Scheme, Professor Shyue Ping Ong is building a connected system of AI, scientific data and automated experiments to change how new materials are discovered.

Joining NUS CDE under the Returning Singaporean Scientists Scheme, Prof Yang Changhuei will build on a career spent expanding the limits of microscopy and biomedical imaging.

Cells can carry a “mechanical memory” of their past surroundings, influencing how efficiently they move through confined spaces.

From coastal resilience to healthcare access and battery reuse, students showed how engineering creativity, teamwork and iteration can turn ambitious prototypes into practical solutions.

A new atom-thin carbon film developed at NUS CDE could help overcome one of the biggest barriers to faster and more energy-efficient microchips.

New method transforms waste from high-performance materials used in aircraft and other structures into aerogels with potential uses in insulation, sound control and environmental clean-up.

New deep learning framework fills gaps in official flood maps, providing a more complete and accurate picture of flood risk in the United States.

By developing a new electrolyte combined with a redesigned electrode architecture, NUS CDE researchers successfully tripled the brightness of electrochemiluminescent (ECL) devices.

Researchers engineer baker’s yeast to sense and respond to different colours of light, enabling new ways to control cellular behaviour with red and blue light.

NUS CDE researchers developed an AI-based framework that traces how Singapore’s shophouse styles evolved, offering new insights for heritage conservation.

Made from two naturally occurring molecules, the material keeps metal conductors attached during movement and enables sensor components to be recovered and recycled after use.