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Four PolyU scholars honoured as RGC Senior Research Fellows and Research Fellows, spearheading innovations in advanced manufacturing, mathematical finance, neuroscience and IoT

The Hong Kong Polytechnic University (PolyU) is committed to pursuing world-leading research and innovation for societal benefits. In the Research Grants Council’s (RGC) Senior Research Fellow Scheme (SRFS) and Research Fellow Scheme (RFS) 2026/27, four distinguished PolyU scholars have been awarded fellowships. The Schemes offer support for the awardees’ continued innovations and breakthroughs in diverse frontier fields, spanning advanced semiconductor manufacturing, mathematical finance, cognitive neuroscience and Internet of Things (IoT) applications. Prof. Christopher CHAO, Senior Vice President (Research and Innovation) of PolyU, extended his congratulations to the awardees and said: “These prestigious fellowships are a resounding testament to PolyU scholars’ outstanding research achievements. Their projects exemplify the University’s determination to pursue research excellence and its commitment to advancing world‑leading innovation. PolyU will continue to cultivate a vibrant research environment, providing significant resources and support for our researchers to focus on frontier R&D. Through innovative solutions, we will continue to create tangible societal benefits while inspiring and nurturing the next generation of research talent to propel Hong Kong’s development as an international innovation and technology hub.” The RGC SRFS and RFS schemes aim to provide sustained research support for outstanding full Professors and Associate Professors with relief from teaching and administrative duties, so enabling them to more fully focus on R&D and nurture the next generation of research talent for Hong Kong. Each of the two schemes award 10 fellowships annually, with awardees being conferred the title “RGC Senior Research Fellow” or “RGC Research Fellow” and provided a grant of around HK$8.5 million and HK$5.6 million respectively. The successful projects showcase the University’s exceptional strength in bridging theoretical breakthroughs with real-life applications, underscoring the world-class calibre of PolyU research and the University’s commitment to translating frontier knowledge into impactful solutions that address pressing global challenges. The PolyU awardees are as follows.

PolyU develops durable shade-stable perovskite–organic tandem solar cells, advancing thin-film solar technology application

It is common for solar panels to be shaded by trees, clouds, birds or buildings. For thin-film solar technologies, however, such shading can cause the shaded areas to develop reverse bias stress (negative voltage), which can reduce power-generation efficiency and even damage the modules of the solar cell. A research team at The Hong Kong Polytechnic University (PolyU) has successfully developed a new generation of perovskite–organic tandem solar cells (POTSCs) that not only deliver high power-generation efficiency but also effectively resist the damage caused by negative voltage. Even under an extreme reverse-bias of –40 V, the tandem devices retain more than 90% of their initial power-generation efficiency, far surpassing all existing thin-film solar technologies — marking a key step towards the practical application of thin-film solar technology. Thin-film solar technologies, such as cadmium telluride (CdTe), copper indium gallium selenide (CIGS), perovskite and organic solar cells, offer the distinct advantages of their light weight, flexibility and cost-effective manufacturing. However, these materials share a common weakness: owing to their electron–ion hybrid conducting properties, once a solar cell is partially shaded and generates negative voltage, its sustained performance becomes difficult and components may even be damaged. The ability to resist reverse bias is therefore key to determining whether thin-film solar technology is durable and capable of stable, long-term operation. Organic solar cells (OSCs) have made significant strides in both efficiency and durability in recent years. Yet their behaviour under reverse-bias condition and underlying charge transport mechanisms in bulk heterojunctions (the power-generating active layer inside the cell, formed by blending two materials), remains largely unexplored by the scientific community. Filling the related knowledge gaps is an indispensable step towards the practical application of thin-film solar technology. Prof. LI Gang, Chair Professor of Energy Conversion Technology of the PolyU Department of Electrical and Electronic Engineering, Sir Sze-yuen Chung Professor in Renewable Energy, and Associate Director of the PolyU Research Institute for Smart Energy (RISE), and his research team have tackled the often-overlooked yet critical aspect of reverse-bias. Prof. Li said, “We have achieved important advances in the stability of OSCs and POTSCs under challenging reverse-bias conditions. Our research makes breakthrough contributions to the understanding of both device operation and durability in organic and perovskite solar technologies.” The reason OSCs are damaged under reverse-bias lies in defects known as deep trap states within the bulk heterojunction. These are invisible traps in the solar cell material that immobilise the charges responsible for power generation, reducing the cell’s efficiency and even causing damage. The team achieved a breakthrough through its innovative approaches and strategic interventions. By suppressing isolated acceptor clusters within the donor-acceptor intermix region (the area at the power-generating core of the cell where the two materials responsible for releasing and receiving charges are blended), the team successfully minimised the above-mentioned defects and developed high-performance OSCs with an irreversible breakdown voltage exceeding -35 V. In other words, as long as the negative voltage does not exceed -35 V, the cell will not be permanently damaged. This substantially enhances damage resistance and establishes a new benchmark for the efficiency and stability of OSCs. The study shows that, by suppressing reverse tunnelling (the phenomenon whereby, when a solar cell is shaded, current flows in reverse, generating negative voltage and damaging the cell) in n-i-p inorganic perovskite-organic tandem solar cells, the organic solar cells successfully protect the perovskite layer. Even after exposure to an extreme reverse-bias of -40 V, the tandem devices retained more than 90% of their initial efficiency. Moreover, these tandem solar cells proved highly stable: after continuous operation at -20 V for 12 hours, they retained 90% of their initial efficiency; and after continuous operation at -4.5 V for 2,000 hours, they retained as much as 97% of their initial efficiency - far surpassing all existing thin-film solar technologies. The research has been published in the paper “Perovskite–organic tandem solar cells with superior reverse-bias stability,” in Nature Materials. The study provides a comprehensive understanding of reverse charge transport mechanism in bulk heterojunctions organic solar cells, overcoming reverse-bias instability in perovskite-based solar cells and providing critical guidelines for developing robust POTSCs. In earlier research, Prof. Li and his team demonstrated the n–i–p inorganic POTSCs achieving an impressive power conversion efficiency (PCE) of 25.9% (certified 25.1%) through bottom contact modulation, with improved stability under various conditions. That study, “Inorganic perovskite/organic tandem solar cells with 25.1% certified efficiency via bottom contact modulation”, was published in Nature Energy in 2025. In the latest study, the n-i-p POTSCs also demonstrated PCE exceeding 26% along with unparalleled reverse-bias stability, advancing their progress towards practical applications. Dr HUANG Jiaming, Postdoctoral Research Fellow and Mr HAN Yu, PhD student, both of the PolyU Department of Electrical and Electronic Engineering are the first authors of the Nature Materials and Nature Energy articles, respectively. Dr REN Zhiwei, Research Assistant Professor of the same department is the co-corresponding author of both publications. Prof. Li added, “The exceptional reverse-bias stability under shadowing conditions has been vividly demonstrated in scalable perovskite-organic tandem solar cell minimodules. This marks a significant leap forward, paving the way for a sustainable and efficient future powered by renewable energy systems.”

PolyU scholar elected ISPRS Fellow 2026 for outstanding contributions to GeoAI and remote sensing

Prof. Qihao WENG, Chair Professor of Geomatics and Artificial Intelligence of the Department of Land Surveying and Geospatial Science at The Hong Kong Polytechnic University (PolyU) and a Global STEM Scholar, has been elected as an International Society for Photogrammetry and Remote Sensing (ISPRS) Fellow 2026. With a strict limit of no more than five Fellows elected globally at any ISPRS General Assembly, the honour recognises his outstanding scientific contributions and international leadership in photogrammetry, remote sensing and geospatial artificial intelligence (GeoAI). This prestigious distinction reflects Prof. Weng’s international standing and PolyU’s strength in advancing AI-enabled geospatial research for environmental and societal impact. His research contributions have significantly shaped the fields of urban remote sensing, urban climate studies, and AI-driven Earth observation, offering crucial data-driven solutions that support sustainable urban development worldwide. Prof. Weng has dedicated his research to urban environmental issues and has significantly advanced the understanding of urbanisation, climate change and environmental sustainability. His pioneering work in sub-pixel analysis, time-series remote sensing imagery and geospatial analytics has had a profound impact on studies of urban heat islands, urban growth and sustainable urban development worldwide. Beyond his fundamental scientific contributions, Prof. Weng has been actively advancing practical applications of GeoAI technologies. His research team integrates AI, earth observation, remote sensing and big data analytics to develop innovative solutions for sustainable urban development, environmental monitoring and urban resilience. Their work supports informed decision-making in diverse areas including transportation, urban planning, public safety, climate adaptation and disaster management. In addition, Prof. Weng leads PolyU Research Centre for Artificial Intelligence in Geomatics (RCAIG) and JC STEM Lab of Earth Observations.  The RCAIG focuses on developing innovative geospatial AI technologies to address environmental and societal challenges in geomatics, with a vision to become a global R&D hub in GeoAI. The JC STEM Lab of Earth Observations is a joint effort of PolyU, Hong Kong Jockey Club Charities Trust, and the Hong Kong SAR government to support the "Global STEM Professorship Scheme". The laboratory focuses on the development of original and innovative Earth Observation (EO) methodologies and technologies and their applications for studies of the causes, effects, and responses to environmental and societal challenges in cities and urban areas, with the goal of becoming a global research hub in EO.  Under his leadership, the research centre and the laboratory have been pushing the frontiers of geospatial intelligence and earth observation, driving transformative solutions for global urban sustainability. This latest fellowship adds to Prof. Weng’s distinguished record of international accolades. He is a Foreign Member of Academia Europaea and an elected Fellow of several of the world's leading scientific organisations, including the Institute of Electrical and Electronics Engineers (IEEE), the American Association for the Advancement of Science (AAAS), the American Association of Geographers (AAG), the American Society for Photogrammetry and Remote Sensing (ASPRS), and the Asia-Pacific Artificial Intelligence Association (AAIA). Furthermore, he serves as Editor-in-Chief of the ISPRS Journal of Photogrammetry and Remote Sensing and Lead of the Group on Earth Observations (GEO)’s Global Urban Observation and Information Initiative, contributing actively to the advancement of the field. Since 2010, the ISPRS Fellowship has been among the highest distinctions in the global photogrammetry, remote sensing, and spatial information science community. It recognises individuals who have made exceptional and sustained contributions to the advancement of the discipline.  

PolyU scholar Prof. Yi-Qing NI receives 16th Guanghua Engineering Science and Technology Award by the Chinese Academy of Engineering

Professor Yi-Qing NI, Yim, Mak, Kwok & Chung Professor in Smart Structures, Chair Professor of Smart Structures and Rail Transit of the Department of Civil and Environmental Engineering, Director of the PolyU-Hangzhou Technology and Innovation Research Institute, and Director of National Rail Transit Electrification and Automation Engineering Technology Research Centre (Hong Kong Branch) at The Hong Kong Polytechnic University (PolyU), has been honoured with the 16th Guanghua Engineering Science and Technology Award by the Chinese Academy of Engineering. The Guanghua Engineering Science and Technology Award is a national award presented biennially and is hailed as “the highest award in China’s engineering sector”. It aims to honour Chinese engineers and scientists who have made outstanding achievements and significant contributions in engineering science and technology, and engineering management. Since its establishment in 1996, the Award has recognised 423 distinguished individuals from different engineering fields. This year,40 awardees were selected from 471 candidates, including one Guanghua Engineering Science and Technology Achievement Award recipient and 39 Guanghua Engineering Science and Technology Award recipients, with Prof. Ni one of the three Award recipients from Hong Kong. Prof. Ni is world-renowned scholar in the fields of structural health monitoring and vibration control. He was ranked in the World’s Top 2% Most-Cited Scientists in rankings released by Stanford University for six consecutive years from 2020 to 2025 (in both the career-long and single year citation categories). He was also ranked among the world’s top 0.05% scholars on the 2025 ScholarGPS Highly Ranked Scholars – Lifetime list and placed fourth globally in the field of “Structural Health Monitoring”. Prof. Ni was nominated by PolyU President and Academician of the Chinese Academy of Sciences, Prof. Jin-Guang TENG. Prof. Teng congratulated him saying, “This award carries profound significance. It not only affirms Prof. Ni’s dedication and outstanding achievements over the years, but will also inspire PolyU staff and students to continue upholding the spirit of innovation in service of the long-term development of the nation and society.” Prof. Ni expressed his gratitude, “I am deeply grateful to the President for his trust and nomination, and I would also like to thank the research team that has worked alongside me over the years. We have always upheld a spirit of continuous innovation and change, starting from real-world needs to advancing smart rail transit and structural safety monitoring technologies, and applying our research outcomes to major infrastructure projects in Hong Kong and in the country more widely. Looking ahead, my team and I will continue to work hard to bring innovative PolyU technologies onto the international stage, deepen collaboration with the Chinese Mainland and overseas partners, enable more people to benefit and make greater contributions to national development and the long-term well-being of society.” Prof. Ni joined PolyU in 2001. His research expertise covers structural health monitoring, structural dynamics and control, smart materials and structures, and sensor technologies. As a core member of PolyU’s multi-disciplinary rail technology research team, he has contributed to the development of fibre Bragg grating sensors that have significantly enhanced the safety and stability of railway services. These devices can be installed on railway tracks and connected to fibre-optic cables, helping maintenance staff more effectively monitor wheel flats and rail conditions, carry out repairs in a timely manner, and safeguard passenger safety. In 2015, PolyU was approved by the Ministry of Science and Technology of the People’s Republic of China to establish the Hong Kong Branch of the National Rail Transit Electrification and Automation Engineering Technology Research Centre, with Prof. Ni serving as Director. The Centre brings together professors from five departments across two PolyU faculties to study high-speed rail from an integrated and macro perspective. Leveraging the internationalisation of China’s high-speed rail, the Centre exports its monitoring systems overseas, thereby promoting Hong Kong’s innovative technologies to the world. Prof. Ni has an outstanding record of research achievements and has received numerous accolades. The monitoring systems he has helped develop have won multiple awards at the Geneva International Exhibition of Inventions in Switzerland and at the China International Industrial Fair. In 2016, the project “Key technologies for building the Canton Tower”, in which he participated, received a second-class State Scientific and Technological Progress Award. Beyond his dedication to academic and scientific research, Prof. Ni is also committed to advancing knowledge transfer. As Director of the PolyU-Hangzhou Technology and Innovation Research Institute, he leads the Institute in focusing on areas such as intelligent transportation, Grand Canal culture and tourism, and medical aesthetics, actively aligning PolyU’s research strengths with local industrial development and societal needs to accelerate the real-world application of research outcomes for the benefit of society. ***END***

Revolutionising building cooling: PolyU’s award-winning AI delivers major energy savings

In Hong Kong, skyscrapers are abundant, leading to significant energy consumption, with cooling systems accounting for more than half of the total power usage. Prof. Fu XIAO, Associate Dean of Faculty of Construction and Environment and Professor of Department of Building Environment and Energy Engineering at the Hong Kong Polytechnic University, has developed an award-winning AI system, which effectively helps reduce up to 40% of daily energy usage, paving the way for a greener and more energy -efficient future. As cities strive towards carbon neutrality, the integration of artificial intelligence (AI) into building management systems is emerging as a game-changer. The ability of AI to process vast streams of data and predict future cooling demands and the performance of a building's energy systems allows it to make real-time, optimised decisions, which offers a promising path to smarter, greener and more cost-effective cooling solutions. Prof. XIAO and her research team's AI-empowered digital twin platform for smart energy management was awarded a Gold Medal at the International Exhibition of Inventions Geneva 2025. This innovation has demonstrated substantial energy savings and operational improvements in various large buildings. Prof. Xiao’s research, titled “An AI-enabled optimal control strategy utilizing dual-horizon load predictions for large building cooling systems and its cloud-based implementation,” was published in Energy and Buildings. The research addressed the limitations of conventional cooling system controls, which typically rely on fixed rules or single-horizon predictions. Such approaches often fail to adapt to the complex and dynamic nature of building cooling demands, leading to unnecessary energy wastage and suboptimal performance. Her innovative AI system introduces a dual-horizon load prediction strategy, leveraging both day-ahead and hour-ahead forecasts to optimise the operation of central cooling plants with multiple chillers. By combining ensemble learning and automatic machine learning (AutoML), the system generates highly accurate, probabilistic predictions of cooling loads, enabling more robust and adaptive control decisions. Unlike traditional systems that might only rely on single-horizon predictions or fixed control rules, this AI solution uses a hierarchical approach. Day-ahead forecasts, based on predicted weather, occupancy and historical data, determine the chiller sequence and the morning start-up time for the entire plant. Hour-ahead predictions, combining real-time data with updated weather forecasts, fine-tune the start and stop times of each chiller and adjust chilled water temperatures. This dual-horizon method ensures that both long-term trends and short-term fluctuations are captured, ensuring more stable and efficient system performance. Supported by the Electrical and Mechanical Services Department (EMSD), the proposed system has been implemented in a high-rise government office building in Hong Kong. The building's cooling system comprises multiple chillers serving both high and low zones, with a sophisticated network of pumps and heat exchangers.  The AI control strategy was deployed via a cloud-based platform, which interfaced with the existing building management system (BMS) using the BACnet protocol—a widely adopted standard for building automation. This setup allowed for seamless data collection, real-time monitoring and AI-driven optimisation, while also maintaining compatibility with the existing BMS infrastructure. Operational data from the BMS were collected at 15-minute intervals and systematically stored for easy access and analysis. A key innovation of the system is its use of ensemble learning and AutoML to develop robust prediction models. Multiple data-driven models are trained independently, each capturing different aspects of the building's thermal behaviour and operational patterns. By combining these models, the AI can improve prediction accuracy and estimate uncertainty, enabling it to make more informed and flexible optimisation decisions.  The performance of the AI-enabled control strategy was rigorously validated through a six-week on-site test during the transition season and early summer. Achieving an average energy saving of 18.4%, the system outperformed conventional rule-based controls, with daily savings ranging from 1.1% to nearly 40%. On a typical test day, the power consumption of the chillers was reduced by up to 21%, and the coefficient of performance (COP) of the chiller plant increased by as much as 47%. These improvements were achieved without compromising thermal comfort, as the system dynamically adjusted to meet real-time cooling demands. Detailed analysis of the test data revealed several key benefits. First, the AI system was able to reduce unnecessary chiller switching by accurately predicting when additional capacity would be needed, thus avoiding the energy wastage associated with frequent start-ups and shutdowns. Second, by optimising the chilled water supply temperature in response to predicted loads, the system improved the efficiency of the chillers. For every 1°C increase in chilled water supply temperature, the chillers achieved energy savings of approximately 3% under ideal conditions while the overall chiller plant saved about 1%. One of the most significant outcomes of the project was its demonstration of practical, scalable AI deployment in existing buildings. The cloud-based implementation required only minor modifications to the BMS and could be rapidly deployed to other sites with similar infrastructure. This rapid deployment capability is crucial for accelerating the adoption of AI-enabled energy management across the building sector. Beyond its implementation in the government office building, the same AI technology has been successfully applied to other large-scale cooling systems. For example, in a recent project supported by the PolyU Carbon Neutrality Funding Scheme, the AI-enabled strategy was deployed in the chiller plant at PolyU. The research, titled “Development of a probabilistic cooling load prediction-based robust chiller sequencing strategy and its real-world implementation,” was published in Applied Energy. The study shows the system reduced the average daily number of chiller switches by 56.5%, achieved daily energy savings of approximately 3,945 kWh and improved the chiller plant's COP by 4.2%. These results further underscore the robustness and generalisability of the approach, highlighting its potential for mass deployment in diverse building types. Source: Innovation Digest   

Brain-inspired electronics: Memristor-based neuromorphic hardware for energy-efficient AI

The emergence of brain-inspired (neuromorphic) computing offers a promising route to overcome the limitations of conventional von Neumann architectures in artificial intelligence (AI). While traditional systems separate memory and computation—resulting in high energy consumption—the human brain integrates these functions efficiently within a compact structure. Addressing this gap, the research from Prof. HAN Suting, Associate Professor of Department of Chemistry at The Hong Kong Polytechnic University, focuses on memristor-based neuromorphic hardware, enabling AI systems that more closely emulate biological intelligence. Memristors are two-terminal devices capable of both storing and processing information, making them ideal for in-memory computing. By continuously adjusting their conductance in response to electrical signals, they mimic the adaptive behaviour of biological synapses. This allows computation to occur directly within memory, eliminating costly data transfer and significantly improving speed and energy efficiency. Through crossbar array architectures, memristor systems perform vector–matrix multiplication—a core neural network operation—in a highly parallel manner. This contrasts with the sequential processing of conventional systems, enabling faster and lower-power computation while supporting synapse-like functionality in hardware. Prof. HAN’s work also incorporates biologically inspired learning mechanisms, particularly spike-timing-dependent plasticity (STDP), enabling adaptive weight updates in memristor arrays. This supports the development of spiking neural networks (SNNs), which more closely resemble natural neural systems. At the materials level, her research explores hybrid perovskite and organic materials, where ion migration enables precise conductance modulation. By optimising crystallinity and introducing passivation layers, her team improves device performance, stability and scalability. Beyond theory, these technologies show strong potential in real-world applications. Flexible, wearable memristor-based systems have been developed for in-sensor computing, integrating sensing, memory, and processing into a single platform. Such systems enable intelligent responses to environmental stimuli, supporting low-power, real-time AI in areas such as healthcare and robotics. Looking ahead, her work extends to human–machine interfaces, including assistive technologies for visual impairments, reflecting a broader vision of compact, brain-like, energy-efficient systems. Together, these efforts position Prof. HAN’s research at the forefront of memristor-based neuromorphic hardware, bridging the gap between silicon systems and biological intelligence.   Source : Faculty of Science Newsletter (June 2026)  

PolyU School of Optometry and HOYA Vision Care strengthen R&D collaboration: New DIMS TED spectacle lenses clinically proven on average to achieve no myopia progression over 12 months

Myopia is a global public health issue. The School of Optometry at The Hong Kong Polytechnic University (PolyU) and HOYA Vision Care have long been committed to developing myopia control spectacle lenses to help safeguard public eye health. Building on more than a decade of collaboration, the two parties have achieved another breakthrough in advancing their patent-protected Defocus Incorporated Multiple Segments (DIMS) technology to launch a new generation of myopia control spectacle lenses featuring the Triple Enhanced Design (DIMS TED). The three key features of DIMS TED are: (1) Defocusing segments positioned closer to the geometric centre of the spectacle lens to activate the near-peripheral retina, identified as highly responsive to the myopic defocus signal that can regulate myopia progression, thereby enhancing myopia control efficacy; (2) Higher defocus power to enable a stronger myopic defocus signal; and (3) an Extended treatment zone that covers a wider peripheral visual field. Clinical studies have confirmed the effectiveness of this innovation. In a randomised controlled clinical trial involving 196 myopic Hong Kong children aged 4 to 12, the average results from the first 12 months of the study demonstrated that children wearing DIMS TED spectacle lenses on average showed no myopia progression, while excessive eye growth was considerably slowed. The main cause of myopia progression was effectively addressed. The study also showed that DIMS TED spectacle lenses are HOYA’s first spectacle lens with reported clinical evidence for effective control of myopia progression from the age of 4 years, as a monotherapy. The findings demonstrate significant benefits for early-onset myopia and underscore the importance of early intervention. This breakthrough sets a new benchmark for myopia control lenses and marks a milestone in the long-standing industry-research-academia collaboration between HOYA Vision Care and PolyU. Prof. Christopher CHAO, Senior Vice President (Research and Innovation) of PolyU, remarked, “PolyU has always been committed to advancing knowledge transfer. Since 2012, we have worked closely with HOYA Vision Care. The development of the DIMS TED spectacle lenses and their clinical study provide strong scientific evidence for early intervention in myopia control, reaffirming PolyU’s global leadership in optometry. We sincerely thank HOYA for their trust in our research capabilities and look forward to strengthening our collaboration to drive commercialisation of further innovations for the benefit of society.” Prof. Dennis TSE, Associate Professor of the PolyU School of Optometry, added, “Our team has built up extensive expertise in myopia control research, particularly in understanding how the eye responds to myopia defocus signals. The new-generation DIMS TED spectacle lenses not only effectively stop myopia progression but also slow down excessive eye growth, with remarkable outcomes in children aged 4 to 6. Importantly, the DIMS TED design maintains the safety profile of the previous generation of lenses, giving parents full confidence to have their children wear them to control myopia and protect eye health.” Mr George KWAN, Managing Director of HOYA Lens Hong Kong Limited, said, “At HOYA Vision Care, we have always been dedicated to advancing evidence-based myopia management solutions. We are delighted to continue driving innovation and achieving breakthroughs through collaboration with PolyU. Since the launch of MiYOSMART in 2018, its patent-protected DIMS technology has earned strong market trust. It is available in over 50 countries worldwide, with more than four million parents choosing it for their children. Our mission is to improve life through vision while continually raising the standard of myopia control. The new generation MiYOSMART iQ featuring DIMS TED offers a more effective, non-invasive solution to help children manage myopia progression. It also enables parents to intervene at an earlier stage, reducing the risk of their children developing high myopia and the associated sight-threatening eye diseases in later life.” Since our collaboration started in 2012, PolyU and HOYA have jointly developed the patent-protected DIMS Technology and launched the first generation of DIMS lenses in 2018, achieving very significant success in myopia control. To further advance this non-invasive technology, the two parties incorporated the Triple-Enhanced Design, leading to the birth of the new DIMS TED lenses. Looking ahead, PolyU and HOYA Vision Care will continue to strengthen their industry-research-academia collaboration and further advance myopia control technologies. Together, we aim to create a clearer future for the next generation and empower children to enjoy better vision and brighter opportunities in life. A parent of a child participant in the clinical study was satisfied with the results, as her child experienced no myopia progression after wearing DIMS TED lenses.

PolyU develops Hong Kong’s first AI agent and risk prediction model for precision diabetes management, with patient recruitment in New Territories West starting in early July

A research team at The Hong Kong Polytechnic University (PolyU) has successfully developed Hong Kong’s first “AI Agent for Precision Diabetes Management – PIPE-AI” (AI Agent), designed specifically for Asian populations, together with a related disease risk prediction model. Leveraging artificial intelligence (AI) and large-scale local electronic health data, the system can more accurately predict the risk of deterioration of complications such as chronic kidney disease in patients with type 2 diabetes over the next 10 years, enabling healthcare professionals and patients to intervene early and improve disease management. The research findings have been published in the leading international journal npj Digital Medicine. To promote the technology’s wider application in the community, the PolyU research team has partnered with the Department of Family Medicine and Primary Healthcare of the Hospital Authority’s New Territories West Cluster, as well as the Yuen Long District Health Centre, to recruit patients with prediabetes and type 2 diabetes in New Territories West from early July to participate in a clinical study of the AI Agent system. Participants will experience personalised risk assessment and health management recommendations firsthand. The study is funded by the Health and Medical Research Fund. Chronic kidney disease is one of the most common and serious complications of type 2 diabetes. As its early symptoms are often not obvious, it is commonly referred to as a “silent killer”. Without early detection and treatment, the condition may progress to uraemia, requiring long-term dialysis or even kidney transplantation. According to local data, the prevalence of diabetes among people aged 65 to 84 is as high as 19%. Diabetes and its complications not only affect patients’ quality of life but also place a heavy burden on families and the public healthcare system. At present, many chronic kidney disease risk prediction models have been developed primarily based on Western population data and may not be fully applicable to Asian populations. A multidisciplinary team led by Prof. YANG Lin, Professor of the School of Nursing at PolyU, used 17 years of electronic health records from the Hospital Authority Data Collaboration Laboratory, covering more than 560,000 diabetes patients, to develop an AI prediction model that is more suitable for Asian populations and which achieves an accuracy rate of 87.1%. The model can analyse patients’ health data and estimate their future risk of developing diabetic complications such as kidney disease, helping healthcare professionals make earlier clinical judgements and arrange follow-up care. In addition to the risk prediction model, the research team has also developed an AI Agent as a “clinical interface” to address the challenge of translating data into concrete action. Focusing on diabetes and complication management, the AI Agent can convert complex medical information into language that is easier for patients to understand, helping them better grasp their health conditions while improving communication between patients and healthcare professionals. The system can be applied in four major scenarios: supporting family medicine and primary healthcare in preliminary screening and risk stratification; assisting specialist outpatient clinics in making more precise referrals for high-risk or complex cases; supporting district health centres in providing 24-hour health consultation services; and helping patients manage their own health, including through diet control, exercise, timely medication adherence and recording of health indicators. To ensure the safety of the system in clinical use, the research team has incorporated a nurse oversight mechanism. When the AI detects abnormal risk levels or important health alerts, the system will automatically notify a registered nurse for further review and follow-up, thereby enhancing the reliability and safety of the system’s application. Prof. David SHUM, Dean of the Faculty of Health and Social Sciences, Yeung Tsang Wing Yee and Tsang Wing Hing Professor in Neuropsychology, Chair Professor of Neuropsychology at PolyU, said, “Diabetes management is not only about treating a single disease, but is also closely related to the long-term allocation of healthcare resources and public health strategy. By translating advanced AI technology into a tool for clinical application, the PolyU research team has extended risk prediction capabilities, which were previously largely confined to hospitals, to primary healthcare and community services. This will help allocate healthcare resources more precisely and drive a shift in the healthcare model from ‘passive treatment’ to ‘proactive prevention’, which in the long run is expected to alleviate the healthcare burden posed by chronic diseases in Hong Kong.” Prof. Yang Lin said, “The patient recruitment programme in New Territories West, launched in early July, marks an important step in bringing smart healthcare into the community in a tangible way. Looking ahead, the team will further integrate imaging and wearable device data to enhance predictive accuracy and will promote the integration of the model into electronic health record systems and district health centre platforms. The initiative will also be expanded to cover other related chronic disease areas, such as the cardiovascular-kidney-metabolic syndrome, so that more members of the public can benefit.”

PolyU co-organised "Open Source and Software Security Forum" to strengthen cybersecurity in the AI era

The Open Source and Software Security Forum, hosted by the Hong Kong Institute of Science and Innovation, Chinese Academy of Sciences, and co-organised by The Hong Kong Polytechnic University (PolyU) and the Hong Kong Cybersecurity Professional Association, was successfully held at the Chiang Chen Studio Theatre at PolyU on 29 June. The forum brought together representatives from top-notch universities, research institutions, and industry from the Mainland and Hong Kong, pooling their wisdom to build a secure, trusted, and vibrant open source technology ecosystem. Prof. CAO Jiannong, Vice President (Education) of PolyU, remarked that open source has become a defining trend in the global software industry, and its development and security must be advanced synergistically. He highlighted PolyU’s ongoing efforts to transform AI education by fostering students' capabilities in active learning, exploration, experimentation, collaboration, and practice. By establishing open source innovation platforms and student open source communities, PolyU aims to encourage students to learn open source technologies, understand the associated risks, and thereby better apply these technologies. During the keynote session, Prof. LUO Xiapu, Associate Dean (Research) of Faculty of Computer and Mathematical Sciences at PolyU, shared insights into the transformative impact of Large Language Models (LLMs) on vulnerability discovery and cybersecurity. He highlighted PolyU’s research achievements in identifying critical vulnerabilities in areas such as blockchain and connected vehicles, significantly improving detection efficiency through AI-powered approaches. Prof. Luo emphasised that an "AI-native" open source security defence system should be built in the future, integrating zero-trust mechanisms throughout the pipeline to uphold the security baseline. In addition, experts from the HKSAR Government's Digital Policy Office, the Cyber Security and Technology Crime Bureau of the Hong Kong Police Force, Fudan University, and the Institute of Software of the Chinese Academy of Sciences delivered insightful presentations on topics ranging from software supply chain security to AI-enabled open source development. PolyU will continue to strengthen collaboration with partners across academia, industry and government to advance secure and trustworthy digital innovation, contributing to the high-quality development of the digital economy in Hong Kong, the Mainland and beyond.   

PolyU ranks third in securing total 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$216.5 million in funding from the General Research Fund (GRF) and the Early Career Scheme (ECS) for 270 projects in 2026/27 under the Research Grants Council, ranking among the top three universities in both total granted amounts and number of projects. A total of 240 PolyU projects have been awarded HK$196.4 million under the GRF, positioning PolyU third among local universities in both total granted amounts and number of projects. In the field of engineering and business studies, PolyU led local universities by securing the highest amount of funding support and 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. In addition, 30 PolyU projects have received HK$20.1 million in funding under 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.