News

SUTD Assistant Professor Ang Yee Sin contributed to the development of a quantum-tunnelling transistor that overcame a fundamental switching limit in conventional transistors, paving the way for more energy-efficient computer and AI chips.

SUTD Assistant Professor Feng Pan co-developed a new algorithm that enabled faster quantum error-correction decoding and demonstrated its capabilities on codes containing up to 1,023 qubits.

SUTD student Anieyrudh R. shared with The Straits Times practical ways to use AI as a learning aid—such as asking it to critique rather than complete one’s work—while Senior Lecturer Sumbul Khan’s Feynman Bot was highlighted as a tool that strengthens understanding by prompting students to explain concepts clearly.

SUTD students Puah Joon Leng and Anieyrudh R., together with Senior Lecturer Sumbul Khan, shared with The Straits Times how the deliberate and responsible use of AI can preserve critical thinking and encourage “productive struggle” in learning.

A multinational team of researchers have built a chip that writes, sorts and electronically reads information stored in the ‘valleys’ of an atomically thin material. Associate Prof Dong Zhaogang is part of the team and was quoted in the article.

A new framework, neural transfer unification, accelerates the training of foundation decoders by aligning decoding tasks across different code sizes. This work was done by researchers from NTU, SUTD, Tokyo University of Agriculture and Technology and Shanghai Jiao Tong University.

Researchers from SUTD and NUS have developed a new computational approach that extends the widely used open-source particle-in-cell method with condensed-matter physics. Associate Professor Wu Lin was quoted in the article.

CNA938 Rewind – Associate Professor Dario Poletti was interviewed for his insights on what quantum computing can and cannot do, and what are its alternatives.

Associate Prof Dong Zhaogang co-led a research team to develop an AI-powered deep-learning framework trained on experimental data rather than simulations, enabling faster and more accurate design of light-controlling nanostructures.

In this new study, an international research team led by Assistant Professor Ang Yee Sin’s team at SUTD, in collaboration with Yangzhou University, China, investigated how silicon-vacancy (SiV) centres respond when the surrounding diamond lattice is compressed or stretched. Using advanced computational modelling, the team systematically explored how the atomic structure and optical signals of the defect evolve under different mechanical conditions.