SENG News

Prof. Lu Mengqian (left) and Dr. Cheng Tat-Fan (right) from the Department of Civil and Environmental Engineering at HKUST unraveled a key summertime atmospheric pattern that is undergoing dramatic changes due to climate change, promising to accelerate subseasonal precipitation extremes and shorten the window for disaster preparedness across the world.
Prof. Lu Mengqian (left) and Dr. Cheng Tat-Fan (right) from the Department of Civil and Environmental Engineering at HKUST unraveled a key summertime atmospheric pattern that is undergoing dramatic changes due to climate change, promising to accelerate subseasonal precipitation extremes and shorten the window for disaster preparedness across the world. 
Groundbreaking Research Reveals Cascading Risks to Food, Water, and Energy Systems
The inauguration of SKL-CRCC is officiated by Prof. Nancy Ip, HKUST President (third right); Prof. Jin-Guang Teng, PolyU President (third left); Prof. Charles Ng Wang-Wai, HKUST Vice-President for Institutional Advancement, Director of SKL-CRCC and CLP Holdings Professor of Sustainability (second right); Prof. Wong Wing-Tak, PolyU Deputy President and Provost (second left); Prof. Li Xiangdong, PolyU Dean of Faculty of Construction and Environment, Director of SKL-CRCC and Director of RICRI (first left); and
The inauguration of SKL-CRCC is officiated by Prof. Nancy Ip, HKUST President (third right); Prof. Jin-Guang Teng, PolyU President (third left); Prof. Charles Ng Wang-Wai, HKUST Vice-President for Institutional Advancement, Director of SKL-CRCC and CLP Holdings Professor of Sustainability (second right); Prof. Wong Wing-Tak, PolyU Deputy President and Provost (second left); Prof. Li Xiangdong, PolyU Dean of Faculty of Construction and Environment, Director of SKL-CRCC and Director of RICRI (first left); and Prof. Yue Qingrui, Chairman of the Academic Committee of SKL-CRCC (first right). 
Gathering Global Experts for Symposium to Tackle Challenges of Climate Change
An HKUST research team led by Prof. Hu Wenqi (left third) and Prof. Xu Qin (third right) develops soft composites with non-reciprocal responses through shear-jamming transitions.
An HKUST research team led by Prof. Hu Wenqi (left third) and Prof. Xu Qin (third right) develops soft composites with non-reciprocal responses through shear-jamming transitions. 
Providing Life-Saving Solution in Emergency Situations
A research team led by Prof. Qu Jianan, Professor of the Department of Electronic and Computer Engineering, School of Engineering, HKUST, has introduced a groundbreaking technique that can capture high-resolution images of the awake mice brain in a near non-invasive manner. The advancement promises deeper insights into human brain function in both healthy and diseased conditions.
A research team led by Prof. Qu Jianan, Professor of the Department of Electronic and Computer Engineering, School of Engineering, HKUST, has introduced a groundbreaking technique that can capture high-resolution images of the awake mice brain in a near non-invasive manner. The advancement promises deeper insights into human brain function in both healthy and diseased conditions. 
Group photo of the research team: Prof. Abhishek K. Srivastava (second right), corresponding author of the study; Liao Zebing (center), PhD student and first author of the study; as well as co-authors including postdoctoral fellow Dr. Maksym Prodanov (first right), PhD students Mallem Kumar (second left) and Song Jianxin (first left). Mr Liao holds a red emitting QR-LED sample.
Group photo of the research team: Prof. Abhishek K. Srivastava (second right), corresponding author of the study; Liao Zebing (center), PhD student and first author of the study; as well as co-authors including postdoctoral fellow Dr. Maksym Prodanov (first right), PhD students Mallem Kumar (second left) and Song Jianxin (first left). Mr Liao holds a red emitting QR-LED sample. 
Prof. Sherry Chen Xian (left), The Hong Kong University of Science and Technology, and Dr. Zhang Chenbo (right), Tongji University, developed FerroAI, a deep learning model that can produce phase diagrams for ferroelectric materials in just 20 seconds. Their findings represent a significant advancement in AI-driven ferroelectric materials research.
Prof. Sherry Chen Xian (left), The Hong Kong University of Science and Technology, and Dr. Zhang Chenbo (right), Tongji University, developed FerroAI, a deep learning model that can produce phase diagrams for ferroelectric materials in just 20 seconds. Their findings represent a significant advancement in AI-driven ferroelectric materials research. 
Artificial Intelligence Empowers Ferroelectric Materials Research
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(圖示一)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。 
A photo of Prof. Chen Hao (right), Director of Collaboration Center for Medical and Engineering Innovation, and Assistant Professor of the Department of Computer Science and Engineering and Department of Chemical and Biological Engineering, and Prof. Liang Li (left), Director of Department of Pathology at Nanfang Hospital and Professor of School of Basic Medical Sciences at Southern Medical University.
A photo of Prof. Chen Hao (right), Director of Collaboration Center for Medical and Engineering Innovation, and Assistant Professor of the Department of Computer Science and Engineering and Department of Chemical and Biological Engineering, and Prof. Liang Li (left), Director of Department of Pathology at Nanfang Hospital and Professor of School of Basic Medical Sciences at Southern Medical University.