Motor imagery or imagined limb movements can power brain–computer interface (BCI) devices, such as prostheses and wheelchairs, supporting rehabilitation for people with neuromusculoskeletal disorders. However, conventional decoding methods often fail to capture complex spatiotemporal variations in electroencephalography signals. Now, researchers from Chiba University, Japan, have developed a novel Embedding-Driven Graph Convolutional Network that decodes dynamic patterns in brain activity, offering improved adaptability and generalizability to advance next-generation BCI technologies.

In a significant advancement for lab-on-chip technology, IBEC researchers in the frame of the European project BLOC, have demonstrated the first integration of a benchtop nuclear magnetic resonance (NMR) spectrometer with a microfluidic cell culture platform capable of real-time metabolic monitoring, made feasible by employing quantum-enhanced NMR techniques to dramatically increase signal sensitivity.

The future for our computers will literally be at the speed of light. Extremely short light pulses can perform ultrafast logical operations: these are the findings of a study recently published in the prestigious journal Nature Photonics. The study was carried out by a group of researchers from the Department of Physics at the Politecnico di Milano, in collaboration with the Istituto di Fotonica e Nanotecnologie (IFN) - Institute for Photonics and Nanotechnologies of the Consiglio Nazionale delle Ricerche (CNR) - National Research Council, and with international research centres.

Amid the growing frequency and intensity of extreme weather events driven by climate change, strengthening disaster preparedness, emergency response, and post-disaster recovery systems has become a global priority. Against this backdrop, the Department of Mechanical Engineering under the Faculty of Engineering at The University of Hong Kong (HKU), in co-organisation with CETIC Foundation, hosted the grand finale of MeckUp Quest 2026 - an AI Robotics Challenge at HKU’s Hui Pun Hing Lecture Hall.

A research team led by Professor Nicholas X. Fang from the Department of Mechanical Engineering from the Faculty of Engineering at The University of Hong Kong (HKU) have developed a world-leading innovation known as “SonoMeta”. This artificial intelligence (AI)-powered MetaLens effectively addresses a longstanding challenge in the medical field, bringing revolutionary advancements in cardiology, pulmonary medicine, and emergency care.

The University of Hong Kong (HKU) has formed a groundbreaking collaboration with three major technology companies, marking a significant step towards bridging the gap between theoretical artificial intelligence (AI) research and practical robotic applications. The strategic partnership, formalised on February 28, 2026, at HKU's Zhangjiang Base, brings together Unitree Robotics, Noitom Robotics, and BrainCo to accelerate the development of embodied intelligence technologies.

A research team led by Professor Nicholas X. Fang from the Department of Mechanical Engineering from the Faculty of Engineering at The University of Hong Kong (HKU) has solved this puzzle using new scientific methods and found an exciting breakthrough. They identified a fundamental physical principle called duality symmetry that sets new limits, and opens new possibilities, for designing ventilated sound-absorbing materials.