News & Stories

The Hong Kong University of Science and Technology (HKUST) research team has developed a groundbreaking wastewater treatment technology that integrates a mesh bioreactor with an ultrasound-induced transient cavitation cleaning mechanism. The system can complete mesh cleaning within 3.8 seconds under anaerobic conditions and achieves 10-20 times higher flux than conventional membrane bioreactors (MBRs). The technology operates efficiently with substantially lower energy consumption, produces treated effluent surpassing international and local discharge standards, and reduces the cost of treating each cubic metre of wastewater to 50% of conventional MBRs, offering a sustainable solution for both municipal and industrial wastewater treatment.

In a critical advance for climate resilience, researchers from The Hong Kong University of Science and Technology (HKUST) have developed an AI model that can predict dangerous convective storms—including Black Rainstorms, thunderstorms and extreme heavy rainfall like those that have hit Hong Kong—up to four hours before they strike. This world-first technology, developed in collaboration with national meteorological institutions and powered by satellite data and advanced deep diffusion technology, improves forecast accuracy by over 15% at the 48‑kilometer spatial scale compared with existing systems. This breakthrough strengthens the overall accuracy of the national weather forecasting system and promises to transform early warning systems for vulnerable communities across Asia.

The Hong Kong University of Science and Technology (HKUST) has demonstrated outstanding research leadership in the 2025/26 Collaborative Research Fund (CRF) and Research Impact Fund (RIF) under the University Grants Committee (UGC)'s Research Grants Council (RGC). The University secured funding for 13 projects under the CRF and RIF, with grants totaling more than HKD77 million. The achievement places HKUST first among all UGC-funded universities in both the number of funded projects and total funding received. This accomplishment highlights HKUST's strength in pioneering interdisciplinary and cross-institutional research, as well as its exceptional capacity for knowledge transfer in translating cutting-edge research outcomes into real-world impact that enhances societal well-being.

Programmable photonics promise faster and more energy-efficient computing than traditional electronics by using light to transmit signals. However, current systems are limited by the need for precise on-chip power monitors. Researchers from the School of Engineering at The Hong Kong University of Science and Technology (HKUST) have developed a germanium-ion-implanted silicon waveguide photodiode. This novel photodetector achieves high responsivity, ultra-low optical loss, and minimal dark current, significantly enhancing the performance of on-chip light monitoring. It provides core hardware for energy-saving and ultra-sensitive biosensing systems, facilitating practical applications in programmable photonics.

The Hong Kong University of Science and Technology (HKUST) and SEMI successfully concluded the inaugural 2025 Semiconductor Innovation and Intelligent Application Summit (SIIAS). As a prelude to the University's 35th anniversary celebrations and supported by the HKSAR Government, the landmark event made its debut in Hong Kong, attracting over 600 semiconductor industry leaders, leading researchers, key policymakers and students from Chinese Mainland, the United States, Saudi Arabia, Germany, Singapore, and beyond. The Summit focused on the latest technological advancements and global development strategies in the semiconductor industry, further solidifying Hong Kong’s position as an international innovation and technology hub. The event underscored HKUST's leadership in semiconductor research and its pivotal role in uniting government, industry, academia, and investors to drive advancement in the sector.

The Hong Kong University of Science and Technology (HKUST) is pleased to partner with SEMI to co-host the inaugural Semiconductor Innovation and Intelligent Application Summit (SIIAS) on December 2, 2025. Supported by the HKSAR Government, this landmark event will be held in Hong Kong for the first time, bringing together global industry leaders, pioneering researchers, and key policymakers to shape the future of semiconductor innovation and drive the industry's strategic development. The SIIAS will further establish Hong Kong as a global innovation hub for microelectronics and advanced manufacturing.

A research team led by the School of Engineering of The Hong Kong University of Science and Technology (HKUST) has made significant advances in quantum rod light-emitting diodes (QR-LEDs), setting record-high efficiency level for red QR-LEDs. This innovation is poised to revolutionize next-generation display and lighting technologies, offering smartphone and television users a vibrant and enhanced visual experience.LEDs have been widely used in electronic products for decades. Recent developments in quantum materials have given rise to quantum dot LEDs (QD-LEDs) and QR-LEDs. QD-LEDs offer superior color purity (color vividness) and higher brightness compared to current mainstream LEDs. However, outcoupling efficiency has now become the primary obstacle, as it sets a fundamental ceiling for external quantum efficiency (EQE), thereby hindering any further performance improvements.

人工智能（AI）圖像編輯及生成模型獲廣泛應用於圖像創作，然而其對抽象概念如感覺和氛圍等理解精準度一直存在局限，且多依賴純文字指令，較難準確表達複雜圖像意思，亦無法捕捉風格、材質或光影等效果。由香港科技大學（科大）馮諾依曼研究院院長兼計算機科學及工程學系講座教授賈佳亞教授帶領的團隊成功開發名為「DreamOmni2」的AI圖像生成和編輯器，不僅擁有卓越的多模態指令編輯和實體物件生成能力，更在抽象概念的理解和生成方面有重大突破，讓AI不僅能「看圖」，更能「理解圖意」，多方面表現優於同類型開源和閉源模型，為AI創作開啟無限可能。直擊缺陷：解鎖抽象概念的創作潛能近年，圖像編輯及生成模型的發展進入爆發階段，新品頻出，但暫時仍未有任何模型能徹底克服實際操作上遇到的兩大缺陷。其一是文本指令的局限性，純文字指令難以準確描述人物特徵、抽象紋理等細節。其二是抽象概念的缺失，現有模型僅能處理有形實體，如人物、物件，無法有效應對髮型、妝容、紋理、光影效果或風格等抽象概念，極大程度上限制了創作空間。DreamOmni2則可解決有關難題，成功執行兩大全新任務，包括根據用家輸入的抽象或實體概念，執行多模態指令編輯和生成，真正成為「全能創作工具」。全面性能測試：超越現有開源與閉源模型在多模態指令生成任務中，DreamOmni2能基於圖片中的實體進行圖像生成，例如提取圖一的畫作掛在臥室牆上，將圖二盤子的材質套用在圖三的水杯，並將水杯放置在桌子上，以生成符合用家要求的新圖像（圖示一）。在多模態指令編輯任務中，DreamOmni2的表現亦非常優秀，例如將圖中帽子的顏色變成與另一張圖毛衣相同的配色（圖示二）。