News & Stories

Multi-sequence knee magnetic resonance imaging (MRI) is an advanced non-invasive diagnostic method for knee pathology. However, MRI interpretation is highly time-consuming and heavily dependent on expertise. A research team from the School of Engineering, the Hong Kong University of Science and Technology (HKUST) has introduced a novel deep learning model which can assist with classifying 12 common types of knee abnormalities, enhancing both efficiency and accuracy. The study was a collaboration between the Smart Lab of HKUST in Hong Kong and the Third Affiliated Hospital of Southern Medical University in Guangzhou, China. Their innovation was recently published in Nature Communications, in a paper titled “Learning Co-Plane Attention Across MRI Sequences for Diagnosing Twelve Types of Knee Abnormalities”.

Signifying the major research collaboration across the two HKUST campuses in Clearwater Bay and Guangzhou, a joint research report series by The Hong Kong University of Science and Technology (HKUST) and The Hong Kong University of Science and Technology (Guangzhou) (HKUST(GZ)) analyzes Hong Kong’s progress and outlines steps to enhance its role as a green finance leader. The research team, composed of experts from both campuses, underscores the necessity for Hong Kong to refine its strategies. By doing so, the city could bolster its competitiveness in the international green finance landscape, thereby positioning itself as a preeminent center for green and sustainable bonds.

In a groundbreaking initiative, The Hong Kong University of Science and Technology (HKUST) has unveiled four AI-driven models poised to transform the medical and healthcare fields. These AI models can assist both general and specialist medical practitioners in diagnosing and prognosing up to 30 types of cancers and diseases, with some achieving accuracy comparable to that of medical experts with five years of experience or more.

A collaborative study in neuroscience, spearheaded by a research team of the Hong Kong University of Science and Technology (HKUST), sheds light on new possibilities for treating central nervous system (CNS) injuries, as published in PNAS*. Through the discovery of a novel gene that regulates the regeneration of multiple types of CNS axons, researchers have achieved a significant stride towards repairing damaged neural networks.

人工智能（Artificial Intelligence，簡稱AI）的出現，令今後的世界將會由三種人組成：即女人、男人和可以跟人交流的機器人！人工智能令人與機器之間能更緊密地協作，將會推動現代社會和人類文明的發展。其深遠影響將遠超過互聯網的出現。勢必重組人類社會各行各業的運作模式。這是一次重大的範式轉移。

A collaborative effort between engineers and biologists at the Hong Kong University of Science and Technology (HKUST) has uncovered a neuroprotective mechanism in spinal cord injury (SCI), shedding new light on therapeutic approaches to potentially benefit millions of patients worldwide. While SCI is a devastating condition with profound, life-altering consequences, unfortunately, a definitive cure remains elusive. For a long time, the study of axon damage and regeneration in SCI has been constrained by the lack of suitable in vivo imaging tools capable of visualizing undisturbed cellular processes within the spinal cord.

To meet the surging demand for high-power AI research sustainably, The Hong Kong University of Science and Technology (HKUST) has launched the city’s largest Liquid Immersion Cooling system in its new research computing facility. This new technology reduces energy consumption for cooling by over 80% and creates an optimal operating environment that can enhance computing performance at lower temperature. High Performance Computing (HPC) is vital for scientific research that involves analyzing vast amounts of data or complex algorithms. However, they consume significant electricity, and excessive heat can hinder their performance.  

HKUST Dean of Engineering Prof. Hong K. LO and his team have developed an award-winning smart traffic control plan to mitigate the notorious congestion in Kwun Tong District, Hong Kong. And they have a broader vision to share in this story.