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PolyU signs MoU with Peking Union Medical College Hospital to advance AI-powered precision diagnosis and treatment for tumors and nurture outstanding medical talent

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PolyU awarded RGC Strategic Topics Grant for advancing next-generation immunotherapy technologies

The Hong Kong Polytechnic University (PolyU) has received funding support from the Strategic Topics Grant (STG) 2025/26 of the Research Grants Council (RGC) to support a multidisciplinary biomedical project aimed at developing an integrated technology platform for next-generation cancer immunotherapy. This pioneering research, which seeks to address some of the most pressing challenges in cancer treatment, has been awarded RGC funding of HK$32.4 million. Although cancer immunotherapy represents a major breakthrough in clinical oncology, it still faces significant challenges. To address some of these, Prof. ZHAO Yanxiang, Associate Head and Professor of the PolyU Department of Applied Biology and Chemical Technology, is leading a multidisciplinary research team to develop a novel integrated approach to unlock the enormous potential of cancer immunotherapy. The project, “An integrated technology platform for next-generation cancer immunotherapy - from identification of tumor neoantigens to development of novel therapeutic vaccine modalities,” has received a total funded budget of HK$36 million, of which RGC funds 90% of the project cost with the remaining 10% matched by the participating universities, over a period of five years. Prof. Christopher CHAO, PolyU Vice President (Research and Innovation), said, “PolyU is at the forefront of medical research and technological innovation, harnessing the strengths of our dedicated scholars, interdisciplinary research excellence, and state-of-the-art facilities and resources. This major funding from the RGC highlights our strong academic and innovative capabilities, particularly in the integration of biomedical technologies and AI-powered healthcare advancements.” Immunotherapy has revolutionised cancer treatment by using the body’s immune system to eliminate tumour cells. Antibodies that function as immune checkpoint inhibitors (ICIs) and chimeric antigen receptor-T cell therapy (CAR-T) have achieved remarkable clinical success, particularly in prolonging survival for some patients. However, these treatment options still face limitations as many cancer types are refractory to ICIs, and CAR-T is mostly effective in blood cancers but not in solid tumours. Recently, neoantigen-based therapeutic vaccine has emerged as a promising new modality in cancer immunotherapy. Some leading candidates, particularly mRNA-based vaccines, have shown encouraging result in early-stage clinical trials. However, challenges such as insufficient immunogenicity of neoantigens and the immunosuppressive tumour microenvironment remain as major hurdles for this approach. To overcome these challenges, Prof. Zhao and the research team proposes to build an integrated technological platform to develop Peptide-based Immunogenic Neoantigen Vaccines (PIN-Vax). This proposed platform has received support from STG under the project topic “Using advanced technology to advance health care challenge.” The platform comprises four interconnected modules that collectively cover the full preclinical development cycle and make use of advanced artificial intelligence technology in an integrated approach. The project plans to first apply the PIN-Vax platform to HPV-associated cervical cancer and HBV-associated hepatocellular carcinoma, as both cancers contain virus-derived neoantigens suitable for vaccine development. The research team will develop a robust pipeline of PIN-Vax candidates and evaluate their anti-tumour efficacy. Combing PIN-Vax candidates with ICIs is also planned to explore further synergistic effect. For future studies, this PIN-Vax platform will be applied in other cancer types, especially those showing limited response to existing ICIs or CAR-T therapy. Prof. Zhao said, “We have brought together an interdisciplinary team of academic researchers, clinicians and industry partners to build the PIN-Vax platform. Our track record and preliminary studies demonstrate the feasibility of this project. Our long-term goal is to transform this platform into an innovative engine for next-generation cancer immunotherapy, benefiting cancer patients.” STG has been set up to support collaborative research in specific areas which can help Hong Kong overcome imminent challenges and tap fast-evolving opportunities. The maximum duration of a project is five years. The ceiling of project cost per project to be awarded by the RGC is $40 million (excluding on-costs).

China Aviation Technology Industry Delegation Visit PolyU

A delegation from China Aviation Technology Industry (Hong Kong) (AVIC) visited PolyU to engage in in-depth discussions on collaboration in aviation technology and artificial intelligence, fostering industry-academia-research integration. PolyU’s Research and Innovation Office showcased the University’s exceptional achievements in academic research, technological innovation, and industry-academia partnerships during the meeting. Prof. HUANG Hailong and Prof. GUAN Yu, both Assistant Professor of the PolyU Department of Aeronautics and Aviation Engineering, along with Prof. ZHANG Xiaoge, Assistant Professor of the PolyU Department of Industrial and Systems Engineering, participated in the meeting. They presented cutting-edge advancements in safe low-altitude flight technology, solutions for thermoacoustic instability, and reliability engineering and trustworthiness assurance for AI-powered intelligent systems, highlighting PolyU’s leadership in these research domains. Mr HAO Weidi, Executive Director and General Manager of AVIC, outlined the company’s strategic priorities and innovative solutions for the low-altitude economy. Mr TAN Fei, Planning Director of Harbin Aircraft Industry Group (HAIG), shared insights into the current state and challenges of the aviation industry.  Following the meeting, the delegation toured PolyU’s Aviation Engineering Laboratory, Research Institute for Artificial Intelligence and Internet of Things, and Aviation Services Research Centre, gaining a deeper understanding of the University’s state-of-the-art facilities and research achievements. This visit established a robust communication platform between AVIC and PolyU, laying a strong foundation for future collaboration in research and technology transfer.  

PolyU and Baosteel establish joint research centre to promote high-quality development of steel industry

The Hong Kong Polytechnic University (PolyU) and Baoshan Iron & Steel Co., Ltd. (Baosteel) have aligned with national strategic priorities by establishing the Baosteel-PolyU Joint Research Centre (BPJC), aiming to develop new quality productive forces in the steel industry. The strategic cooperation agreement was signed yesterday at the PolyU campus, followed by a plaque unveiling ceremony for BPJC, marking the launch of a comprehensive industry-academia-research partnership between the two organisations. Witnessed by Prof. Jin-Guang TENG, PolyU President and Mr ZOU Jixin, Chairman of Baosteel, the strategic cooperation agreement was signed by Prof. Christopher CHAO, PolyU Vice President (Research and Innovation), and Mr MAO Xiaoming, Vice President of the Baosteel Central Research Institute. Following the signing ceremony, Prof. Teng and Mr Zou jointly unveiled the plaque to mark the occasion. Subsequently, Prof. Jianguo LIN, Chair Professor of Materials Technologies of the PolyU Department of Industrial and Systems Engineering and Director of BPJC outlined the Centre’s vision and research projects. Prof. Jin-Guang Teng said, “This strategic cooperation will leverage PolyU research strengths and Baosteel’s industry resources and experience, helping to overcome key technological bottlenecks, advance the industry’s goal of achieving efficient and green production, and inject new momentum into Hong Kong’s development as an international innovation and technology centre. By strengthening industry-academia-research collaboration and innovation, both organisations will promote the development of new quality productive forces and propel sustainable industrial advancement.” Mr Zou Jixin said, “Baosteel and PolyU have joined forces with their complementary strengths to establish the BPJC – a strategic initiative rooted in their shared vision for the future of the steel industry. This partnership will focus on practical applications and cutting-edge technological development, bringing together resources to achieve breakthroughs in original and pioneering technologies and strengthening translational research capabilities. It will drive upgrade of the steel industry value chain and contribute to Hong Kong’s development as an international innovation and technology centre.” BPJC will gather top talent to conduct strategic, forward-looking and basic research while accelerating the translation of research outcomes into practical solutions. By strengthening international exchanges and cooperations, it will set new standards for university-industry collaboration on innovation.

PolyU-Daya Bay Technology and Innovation Research Institute establishes Artificial Intelligence Research Centre, facilitating Huizhou’s smart industrial transformation

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PolyU ranks third among universities in securing funding from the General Research Fund and Early Career Scheme for academic and research excellence

The Hong Kong Polytechnic University (PolyU) has received a total of HK$213.3 million in funding from the General Research Fund (GRF) and the Early Career Scheme (ECS) for 237 projects for 2025/26 under the Research Grants Council, ranking among the top three universities in both total granted amounts and number of projects. A total of 212 PolyU projects have been awarded grants amounting to HK$195.1 million from the GRF, positioning it as the third-highest among local universities in both total granted amounts and number of projects. In the field of engineering, PolyU stands out among universities by securing the largest amount of funding support and projects, reaching HK$103.2 million for 99 projects. The GRF aims to supplement universities’ own research support to researchers who have achieved or have the potential to achieve excellence. It covers two areas of research focused on broad knowledge enhancement and specific purposes. A total of 25 PolyU projects have been funded amounting to HK$18.2 million from the ECS. The ECS aims to nurture junior academics and prepare them for a career in education and research. Scientific and scholarly merit, and qualification and track record of the principal investigator are among the assessment criteria. 

Professor Christopher Chao receives prestigious ASHRAE Louise and Bill Holladay Distinguished Fellow Award 2025

The Hong Kong Polytechnic University (PolyU) is proud to announce that Prof. Christopher CHAO, Vice President (Research and Innovation) and Chair Professor of Thermal and Environmental Engineering, has been awarded the esteemed Louise and Bill Holladay Distinguished Fellow Award 2025 from the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). This prestigious recognition was presented at the ASHRAE Annual Conference in Phoenix, Arizona, USA on 21 June 2025. Founded in 1894, ASHRAE is a global professional society committed to serving humanity by advancing the arts and sciences of heating ventilation, air conditioning, refrigeration and their allied fields. The ASHRAE Louise and Bill Holladay Distinguished Fellow Award, initiated in 1979, honours individuals for their continuing preeminence in engineering and research work. As one of ASHRAE’s most prominent awards, the Louise and Bill Holladay Distinguished Fellow Award is presented to one Fellow each year, or sometimes not awarded at all if no suitable nominee is identified. Prof. Chao is the third recipient from Asia to receive this distinguished honour, joining professors from the University of Hong Kong and the National University of Singapoe. As the only awardee invited to deliver his acceptance speech on stage, Prof. Chao stated, “I am deeply honoured to receive this recognition from ASHRAE. This award reflects not only my work but also the dedication and innovation of my colleagues at PolyU over the years. Together, we strive to advance research and innovation in the field of building energy and environment, contributing to the academic and professional communities that inspire us to push the boundaries of engineering excellence.” Prof. Chao’s research integrates intelligent building systems with infectious disease prevention. Using AI-driven energy optimisation, he creates infection-resilient, energy-efficient environments. This dual focus positions smart buildings as essential for health and sustainability. This recognition of Prof. Chao’s work underscores PolyU’s commitment to excellence in research and innovation, reinforcing its status as a leading university in the region. His contributions to the field, particularly in sustainable building technologies, have made a significant impact on both academic and practical applications. For more information about the ASHRAE Louise and Bill Holladay Distinguished Fellow Award, please visit ASHRAE’s official website.

Tea and the gut: Unlocking health through its bioactive compounds

Tea, made from the Camellia sinensis plant, is one of the most widely consumed beverages in China and globally. Beyond its cultural significance, tea is rich in bioactive compounds such as polyphenols, polysaccharides, caffeine, and especially epigallocatechin gallate (EGCG), a potent antioxidant linked to numerous health benefits. Prof. GAN Renyou, Assistant Professor in the Department of Food Science and Nutrition of The Hong Kong Polytechnic University, focuses his research on exploring how these compounds interact with the gut microbiota, which plays a vital role in breaking down tea components and enhancing their bioavailability and bioactivities. EGCG, for instance, is poorly absorbed in its original form. But colonic bacteria can convert it into more absorbable metabolites, amplifying its in vivo effects, supporting cardiovascular health and potentially preventing cancer. Another key focus of Prof. GAN’s research is tea fermentation. The six main types of tea—green, yellow, white, oolong, black, and dark—undergo varying degrees of fermentation, each producing distinct chemical profiles. For instance, the unfermented green tea retains higher levels of catechins like EGCG, while the post-fermented dark tea yields theabrownins with unique ingredients that can fight against non-alcoholic fatty liver disease and obesity. While regular tea consumption is linked to benefits such as improved cardiovascular health, better blood sugar regulation and cognitive support, Prof. GAN cautions against excessive use of concentrated green tea extracts, which may lead to adverse effects like liver damage. His work aims to identify safe and effective dosages, especially for use in supplements. Tea’s expanding role in functional foods, beverages and even cosmetics, highlights its commercial and therapeutic values. Prof. GAN’s previous experience with patents further supports the development of tea-based bioactives for the health and wellness industries. Although his findings are largely based on in vitro and animal studies, they lay a strong foundation for future clinical research. In China, where tea is both a daily ritual and a traditional remedy, his work bridges ancient practices with modern science - promoting tea as a powerful tool for preventive healthcare. Finally, tea can be considered as a typical example of “Food as Medicine”. Source: PolyU Science Newsletter  https://www.polyu.edu.hk/fs/publication/e-newsletter/issue-6/interview---fsn/

Innovating Echocardiography Video Segmentation with Temporal and Noise-resilient Techniques for Refined Cardiovascular Diagnostic Imaging

A Novel Approach to Overcoming Challenges in Ultrasound Imaging Using Advanced Memory Prompting   Cardiovascular diseases are a leading health concern in Hong Kong, prompting many to undergo regular heart check-ups for their early detection and management. Echocardiography, a key diagnostic imaging tool, plays a crucial role in assessing heart function, offering non-invasive insights into cardiovascular health and aiding in timely intervention. However, interpreting these ultrasound images manually is challenging due to speckle noise and ambiguous boundaries, requiring significant expertise and time. Consequently, a heart check-up is rarely included in a regular annual body check scheme.    Prof. Harry QIN, Professor of the School of Nursing at The Hong Kong Polytechnic University, and his team have developed a novel model, MemSAM, which aims to revolutionise echocardiography video segmentation by adapting the artificial intelligence (AI) model Segment Anything Model (SAM) from Meta AI to meet the specific demands of medical imaging.    MemSAM introduces a unique approach to echocardiography video segmentation through a temporal-aware and noise-resilient prompting scheme. Released by Meta, SAM is an advanced AI model dedicated to image segmentation which can quickly identify elements in any image and segment the elements.  While traditional SAM applications excel in natural image segmentation, their direct application to medical videos has been limited due to the lack of temporal consistency and the presence of significant noise. MemSAM addresses these issues by incorporating a space-time memory mechanism that captures both spatial and temporal information, ensuring consistent and accurate segmentation across video frames.  The introduction of MemSAM has the potential to substantially mitigate financial and specialised expertise requirements, potentially alleviating the burden associated with prolonged wait times for advanced cardiac imaging modalities. Furthermore, it could enable the incorporation of simplified cardiac assessments into routine health screenings, enhancing accessibility and early detection.     Echocardiography videos are notoriously difficult to segment due to several inherent challenges. The presence of massive speckle noise and numerous artifacts, coupled with the ambiguous boundaries of cardiac structures, complicates the segmentation process.  Moreover, the dynamic nature of heart movements results in large variations of target objects across frames. MemSAM's memory reinforcement mechanism enhances the quality of memory prompts by leveraging predicted masks, effectively mitigating the adverse effects of noise and improving segmentation accuracy.  A standout feature of MemSAM is its ability to achieve state-of-the-art performance with limited annotation. In clinical practice, the labour-intensive nature of annotating echocardiographic videos often results in sparse labelling, typically restricted to key frames such as end-systole and end-diastole. MemSAM excels in a semi-supervised setting, demonstrating comparable performance to fully supervised models while requiring significantly fewer annotations and prompts.   MemSAM's efficacy has been rigorously tested on two public datasets, CAMUS and EchoNet-Dynamic, showcasing its superior performance over existing models. The model's ability to maintain high segmentation accuracy with minimal prompts is particularly noteworthy, highlighting its potential to streamline clinical workflows and reduce the burden on healthcare professionals.   The technology behind MemSAM is rooted in the integration of SAM with advanced memory prompting techniques. SAM, known for its powerful representation capabilities, has been adapted to handle the unique challenges posed by medical videos. The core innovation lies in the temporal-aware prompting scheme, which utilises a space-time memory to guide the segmentation process. This memory contains both spatial and temporal cues, allowing the model to maintain consistency across frames and avoid the pitfalls of misidentification caused by mask propagation.   The memory reinforcement mechanism is another critical component of MemSAM. Ultrasound images are often plagued by complex noise, which can degrade the quality of image embeddings. To counter this, MemSAM employs a reinforcement strategy that uses segmentation results to emphasise foreground features and reduce the impact of background noise. This approach not only enhances the discriminability of feature representations but also prevents the accumulation and propagation of errors in the memory.   MemSAM's architecture is built on SAMUS, a medical foundation which is in turn a model based on SAM and optimised for medical-used images. The model processes videos in a sequential frame-by-frame manner, relying on memory prompts rather than external prompts for subsequent frames. This design minimises the need for dense annotations and external prompts, making it particularly suited for semi-supervised tasks.   While MemSAM represents a significant leap forward in echocardiography video segmentation, future research aims to enhance the model's robustness, particularly in scenarios where initial frame quality is poor. Additionally, exploring the application of MemSAM across other medical imaging domains and optimising its computational efficiency are exciting avenues for further development.    MemSAM not only addresses the longstanding challenges of ultrasound video segmentation but also sets a new benchmark for integrating advanced machine learning techniques into medical imaging. By bridging the gap between cutting-edge technology and clinical application, MemSAM holds the promise of improving diagnostic accuracy and patient outcomes in cardiovascular care. This innovative model exemplifies the potential of AI to revolutionise healthcare, offering a glimpse into a future where automated, accurate and efficient diagnostic tools are the norm.    Source: Innovation Digest

PolyU research projects win funding support from RAISe+ Scheme

The Innovation and Technology Commission of the HKSAR Government has recently announced the second batch of projects selected for funding under the Research, Academic, and Industry Sectors One-plus (RAISe+) Scheme. Among the successful projects, four from The Hong Kong Polytechnic University (PolyU) showcase the University’s research excellence and strong commitment to commercialisation of its research outcomes. Prof. Christopher CHAO, PolyU Vice President (Research and Innovation) congratulated the PolyU research teams, stating, “We are delighted that four PolyU research projects have been named among the second batch of those funded under the RAISe+ Scheme. This achievement not only underscores the University’s robust research capabilities, but also the strong confidence that government, industry and community stakeholders have placed in our ability and efforts in driving innovations and translation of research outcomes. Moving forward, PolyU will continue to foster effective collaboration among the Government, industry, academia and research sectors, injecting new momentum into its research projects and accelerating the translation of research outcomes into real-world impact, which in turn contributes to the development of Hong Kong, our Nation and the world.” The funded projects cover a wide range of innovation and technology fields, including AI and robotics, Chinese medicine, computer science/information technology, and electrical and electronic engineering. Details of the projects are listed below Project Title Project Leader Project Description High-Speed 3D Stacked AI Vision Sensors Prof. Yang CHAI Associate Dean, Faculty of Science; Chair Professor of Semiconductor Physics, Department of Applied Physics; and Director, Joint Research Centre for Microelectronics This project focuses on the development and commercialisation of an advanced AI vision sensor with high-speed operation, high dynamic range, and ultra-low power consumption. The sensor overcomes key limitations of conventional image sensors, particularly motion blur in high-speed scenarios. Key applications of the AI vision sensor include security surveillance systems, autonomous navigation, and motion analysis in extended reality devices and smartphones. The sensor achieves high-speed, high-dynamic-range, and low-power imaging through the integration of conventional image sensors with dedicated visual information processing chips. Novel Nutraceuticals for Neurodegenerative Diseases Prof. Simon Ming-yuen LEE Cally Kwong Mei Wan Professor in Biomedical Sciences and Chinese Medicine Innovation; Chair Professor of Biomedical Sciences, Department of Food Science and Nutrition; and Director, PolyU-BGI Joint Research Centre for Genomics and Synthetic Biology in Global Ocean Resources This project develops novel nutraceuticals and drugs derived from natural resources for treating neurodegenerative diseases. It establishes the LifeChip technology platform, combining next-generation DNA sequencing, AI-driven discovery, advanced chemical separation, high-throughput in vivo screening, and synthetic biology. Focusing on neurodegenerative diseases like Alzheimer’s and Parkinson’s, as well as neurological disorders including insomnia, depression, and anxiety, this integrated approach delivers a comprehensive solution for both prevention and treatment using innovative nutraceuticals with unique mechanisms of action. For instance, the development candidate Oxyphylla® is a first-in-class drug targeting α-synuclein, an emerging therapeutic target for Parkinson’s disease. Oxyphylla® is anticipated to become a disease-modifying therapy, offering a breakthrough in neurological health. Reallm: World-leading Enterprise GenAI Infrastructure Solution Prof. YANG Hongxia Executive Director, PolyU Academy for Artificial Intelligence;Associate Dean (Global Engagement), Faculty of Computer and Mathematical Sciences; and Professor, Department of Computing   The project aims to develop a comprehensive Generative Artificial Intelligence (GenAI) infrastructure solution, including by: establishing a decentralised pretraining and post-training system architecture to support distributed model training frameworks; developing a domain-adaptive continual pretraining and post-training system to continuously optimise large language models using domain-specific unlabelled data, enabling adaptation to target domain distributions; and designing a low-bit training framework that requires only half the computational and storage resources of traditional training, while still achieving high-quality, end-to-end training from pretraining to post-training—significantly lowering the entry barrier for enterprises. Ultimately, the project will launch a platform specifically designed to enhance cross-domain collaboration through enterprise-grade GenAI services, including Software-as-a-Service, Platform-as-a-Service, and Infrastructure-as-a-Service. Tunable Laser Chip Based on Metasurface Structure and its Application Prof. YU Changyuan Director, PolyU-Jingjang Technology and Innovation Research Institute; and Professor, Department of Electrical and Electronic Engineering   This project pioneers a novel broadband tunable laser chip that, for the first time, integrates both a metasurface reflector and phase-change materials within a vertical-cavity surface-emitting laser. This enables an ultra-high quality factor resonant cavity and dynamic continuous tuning of the output wavelength over an exceptionally wide bandwidth (40nm). Compared to traditional laser structures, the chip not only features a more compact design but also achieves the same kHz-level tuning speed as leading international competitors. With the cost just one-twentieth that of existing market solutions, the chip is expected to achieve widespread adoption in battery monitoring systems, industrial production processes, autonomous driving technologies and high-speed optical communication modules. Inaugurated in 2023, the RAISe+ Scheme aims to provide funding, on a matching basis, for at least 100 research teams from universities funded by the University Grants Committee which demonstrate strong potential to evolve into successful startups. Each approved project will receive funding support ranging from HK$10 million to HK$100 million.