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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.   

PolyU develops intelligent traffic signal control system supported by Smart Traffic Fund

The Hong Kong Polytechnic University (PolyU) continues to advance innovative solutions that tackle real‑world challenges and contribute to a smarter future. In the 25th batch of the Smart Traffic Fund, a PolyU project was awarded approximately HK$3.578 million in funding to develop an intelligent traffic signal control system for temporary traffic arrangements using real-time sensing technologies. This innovation will provide the industry with a flexible and efficient solution for temporary traffic management. Led by Prof. CHUNG Chin-shin Edward, Professor of the Department of Electrical and Electronic Engineering at PolyU, the project “Development of an Intelligent Signal Control System for Temporary Traffic Arrangement” secured funding of approximately HK$3.578 million for 24 months. This project focuses on developing an intelligent portable traffic light system tailored for the one-lane-two-way temporary traffic arrangement. To address common bottlenecks during roadworks on narrow streets in Hong Kong, the project will develop advanced sensing technologies for real-time monitoring of queues and traffic flow, and establish a dynamic traffic flow model. The system will apply adaptive signal control algorithms to dynamically adjust signal timings based on real-time demand, reducing traffic queues and preventing gridlock. The deliverables include a mobile prototype system that provides a flexible, efficient temporary traffic management solution for the industry. PolyU has long been committed to the research and application of vehicle-related innovation and technology, with 33 projects supported by the Smart Traffic Fund to date. This achievement underscores the University’s contribution to advancing transportation technology innovation. The Smart Traffic Fund provides funding support to local organisations and enterprises for conducting research and applying innovation and technology with the objectives of enhancing commuting convenience, enhancing efficiency of the road network or road space, and improving driving safety.

Innovating for the future: Pioneering predictive fire‑safety technologies for sustainable cities

Resilience against fire hazards is essential for sustainable urban development, especially in dense and complex environments within big cities, where fire risks are evolving rapidly. By leveraging smart city technologies, such as data‑generating networks, real‑time monitoring, and physics‑ and AI‑based predictive analytics, Prof. Asif Sohail USMANI, Chair Professor in Building Sciences and Fire Safety Engineering of the Department of Building Environment and Energy Engineering of The Hong Kong Polytechnic University (PolyU), has developed the SureFire forecasting tool, an intelligent system for fire safety and public emergency management across urban infrastructure and the built environment. This tool integrates native sensing capabilities in buildings with distributed sensors to monitor fire progression in real time and forecast critical events through AI-assisted simulations during severe incidents, enabling emergency responders to make informed decisions. SureFire also holds the potential to empower next‑generation firefighting robots, enabling fully automated, casualty‑free firefighting in the future. At PolyU, we continue to drive innovation that strengthens urban safety and builds a more resilient, sustainable future.  

PolyU leverages AI and research strengths to empower the I&T Ecosystem in the Northern Metropolis

Organised by Metro Broadcast Corporation Limited and fully supported by The Hong Kong Polytechnic University (PolyU), the "AI+ Innovation Awards & Future Impact Summit 2026” was successfully held on 24 June. The event aimed to promote the realisation of new quality productive forces, explore the development of the Northern Metropolis, and deepen the "Finance+" advantages, while commending outstanding leaders in the innovation and technology (I&T) sector. Prof. Christopher Chao, Senior Vice President (Research and Innovation) of PolyU, served as a guest speaker in the panel discussion titled "Northern Metropolis Engine — Viewing the AI Industry Cluster from the Hong Kong-Shenzhen Innovation and Technology Park". He engaged in an in-depth dialogue with leaders from the Hong Kong-Shenzhen Innovation and Technology Park and Microsoft, a leading global technology company, to jointly analyse the latest developments and future opportunities in Hong Kong's I&T ecosystem. During the forum, Prof. Chao shared PolyU's core strategies and forward-looking layout under the development blueprints of the Northern Metropolis and the Loop region. He stated that Hong Kong is actively leveraging its advantage as a “Super Connector” to unite Greater Bay Area partners and build a unique tripartite collaboration model of overseas algorithms, mainland data, and Hong Kong compliance. He added that PolyU's Academy for Artificial Intelligence (PAAI) is committed to developing low-cost, high-efficiency, cutting-edge algorithm technologies to accelerate the integration of AI into various industries. Meanwhile, he emphasised the need to accelerate the establishment of the University Town in the Northern Metropolis to create a sustainable I&T talent ecosystem, providing an inexhaustible driving force for the scientific research development of Hong Kong and the Nation. The event also featured the 'Hong Kong AI+ and I&T Awards,' honouring entrepreneurs and professionals who successfully leveraged AI for business transformation. Categories included I&T leadership, enterprise applications, social impact, and 'new quality productive forces. Furthermore, to further popularise I&T knowledge, five experts from PolyU participated in a four-episode interview series on Metro Finance's program “AI Evolution”. The series will delve into the latest applications and future trends of AI in four key sectors (Finance, Healthcare, Elderly care, and Education). The program will be broadcast sequentially starting in mid-July, so please stay tuned. Looking ahead, PolyU will leverage its research strengths to deepen industry-academia-research collaboration with enterprises and institutions in the Northern Metropolis, driving I&T synergy across the Greater Bay Area.  

PolyU scholar wins HUAWEI Spark Award, highlighting University’s strengths in research translation and industry collaboration

The Hong Kong Polytechnic University (PolyU) has once again gained international recognition from top-tier global technology enterprise for its research and innovation excellence. Prof. Minchen Tommy WEI, Associate Head of the Department of Building Environment and Energy Engineering and Director of the PolyU-Qianhai Disruptive Technology and Innovation Research Centre (QHRC), was recently honoured with the prestigious HUAWEI Spark Award in recognition of his team’s innovative solution to a major industrial technology challenge and its successful translation of cutting-edge research findings into real-world industrial applications. Prof. Wei is the second PolyU scholar to receive this honour, and notably, the only scholar from a Hong Kong tertiary institution to be awarded over the past two years. Previously in 2023, Prof. WANG Zuankai, PolyU Associate Vice President (Research) and Chair Professor of Nature-Inspired Engineering in the Department of Mechanical Engineering, received the same honour for his innovative solution on transparent and wear-resistant super-sparse surfaces. These consecutive accolades underscore PolyU’s world-class capabilities in driving research translation, as well as its achievements in knowledge transfer and industry-academia-research collaboration as recognised by a global technology leader. Prof. Christopher CHAO, PolyU Senior Vice President (Research and Innovation), extended his warm congratulations to Prof. Wei. He stated, “Prof. Wei’s HUAWEI Spark Award once again demonstrates PolyU’s strategic commitment to innovative research and market application. The University remains dedicated to fostering deep integration between academic and industry, and driving innovative venture through cross-border collaboration. Through a robust knowledge transfer framework and innovation ecosystem, we will continue to accelerate the commercialisation of research outcomes to create value for industry upgrading and social development.” Established by HUAWEI in 2021, the Spark Award focuses on fundamental research in areas including information and communications technology, materials science and mathematical algorithms. Under the initiative, Huawei identifies industrial challenges with significant commercial and scientific value and invites universities worldwide to develop original solutions, recognising researchers whose innovations advance both science and industry. Prof. Wei and his team have long dedicated on the underlying mechanisms of the human visual system, translating research findings into innovative solutions for full-link multimedia systems ranging from camera capture to screen display. Addressing a major bottleneck in display colour calibration for this year’s HUAWEI challenge, the team leveraged visual science research to deliver a breakthrough engineering solution. This innovation significantly enhances the colour calibration accuracy and user experience of product displays. The technology has already been deployed, making a tangible contribution to the advancement of display technology worldwide. To further accelerate research translation, Prof. Wei co-founded the start-up Guardian Glow Limited, which specialised in developing artificial intelligence-powered personal health-monitoring devices, as well as key technologies for extended reality (XR) devices. The start-up has now established its presence at the QHRC. Prof. Christopher Chao added, “The successful transformation of Prof. Wei’s pioneering research into high-end technology products demonstrates the pivotal bridging role played by QHRC. The Centre serves not only as an important gateway for connecting PolyU’s research with Mainland industrial chains, but also stands as a core platform for our commercialisation strategy, helping laboratory innovations seamlessly enter the market.” This achievement also highlights PolyU’s broader commitment to enhancing research impact and expanding its comprehensive knowledge transfer network. To date, the University has established 12 Mainland Translational Research Institutes (MTRIs) in cities across the Chinese Mainland, precisely aligning PolyU’s research strengths with local industrial development and societal needs. Prof. Christopher Chao stated, “PolyU has established a nationwide network for research translation, anchored by five major innovative platforms in the Guangdong-Hong Kong-Macao Greater Bay Area — Qianhai, Futian, Nanshan, Huizhou and Zhongshan — alongside other innovation platforms across the country. These initiatives consistently provide scientific backing for local economic growth and industrial upgrade, levering the power of innovation to serve national development.” While continuing strengthening its footprint in the Chinese Mainland, PolyU is also actively expanding its global innovation network. The University will continue to strengthen its knowledge transfer strategy by establishing innovation and entrepreneurship hubs both locally and overseas. By leveraging the distinct advantages of academia, research and industry, the University aims to drive market-oriented innovation, foster cross-disciplinary and cross-regional collaboration, and contribute to global technological advancement and long-term sustainable societal development.