NOV 2025 Volume 27 No.1 PRIVACY IN THE DIGITAL AGE Is protection possible? Ancient genes, modern miracles Billion-year-old molecular tools unlock the power of stem cells Guided by nature Engineers mimic bird agility to boost drone speed and safety
Contents 02 04 06 08 10 12 Privacy in the Digital Age Keeping Data under Wraps When Privacy Is Threatened A Catch-22 for Consumers A Better Way to Share Giving for the Greater Good Cover Story 14 16 18 20 22 24 26 28 With Flying Colours Brain Waves On the Nose Designer Genes Does AI Have a Mind? Moving Pictures Green Screen Star Signs Research 30 32 Dream Big, Start Small, Learn Fast Training Guardians of Heritage Teaching and Learning 34 36 38 Pearls of Wisdom Early Warning System Safe to Swallow Knowledge Exchange 40 42 44 46 48 Keeping the Wheels Turning Agent of Change HKU’s Networker-in-Chief An Enviable Challenge Students’ Advocate People 50 The Thriving Dark Web Books
Being online inevitably means giving up personal information to access websites and services, whether willingly or not. So how can privacy be protected? And what are the limits to that protection? HKU scholars have been exploring the implications of this digital dilemma from engineering and legal perspectives, and its impact in business and medicine. PRIVACY IN THE DIGITAL AGE HKU Bulletin | Nov 2025 Cover Story 2 3
HKU Bulletin | Nov 2025 Cover Story 4 5 Moving in the right direction The third approach for protecting privacy is differential privacy. This is for situations when people want to ask specific questions of raw data, rather than share. Protection can come from tracking and controlling the questions to protect privacy. For instance, a person investigating lung cancer in Hong Kong might ask the database for rates among HKU employees and then among employees in computer science and so on, in a way that narrows down an individual’s identity. Differential privacy adds ‘noise’, or a layer of cybersecurity, to prevent that from happening. Despite the limitations of these technical solutions, Professor Yiu is optimistic they are advancing in the right direction to protect privacy and enable greater data sharing, particularly as encryption technology is more widely used. But he is concerned that the law still lags behind. For instance, privacy law is vague on whether data encrypted through homomorphic encryption can be sent abroad. “If data is encrypted, then the data is protected. But can I still send it out? The privacy law in Hong Kong does not talk about this very clearly,” he said. Professor Yiu has been advising Hong Kong’s Office of the Privacy Commissioner for Personal Data, the Hong Kong Police Force of the Government of the Hong Kong Special Administrative Region of the People’s Republic of China and many others on the societal benefits of allowing datasharing technologies to be used more widely. “The technology can help resolve a lot of things, but we cannot achieve the benefits of these solutions if the laws and regulations do not allow us to use it. We also need more education so that everybody can accept it,” he said. Professor Yiu Siu-ming Balancing privacy with research and community development has become a very big challenge. But I believe that technology and the law, together, can resolve the problem. Rapid progress in data technology, including AI, means more personal data than ever is being collected – whether it be DNA, facial recognition or any human identifier or activity. For individuals, that raises obvious privacy concerns. But Professor Yiu Siu-ming of the School of Computing and Data Science is not so easily discouraged. Professor Yiu has studied data protection and privacy for years. He believes the risks are surmountable with the right tools and support and an appreciation of the value of data collection to society, which can be used to develop new health treatments, improve national security and facilitate business management, among many other things. “The whole world is increasingly concerned about privacy. Balancing privacy with research and community development has become a very big challenge,” he said. “But I believe that technology and the law, together, can resolve the problem.” On the technology side, he has been working on three methods to transfer data without disclosing the data source and thus protecting privacy. While not yet perfect, they offer different kinds of data protection under different circumstances. The data goldrush is putting pressure on personal privacy, as everyone from businesses to universities to governments seeks to mine and share data on individuals for profit, research or policy development. But those privacy concerns may be hindering non-intrusive solutions that could help advance research and benefit society, says computer scientist Professor Yiu Siu-ming. Keeping Data under Wraps Options for protection One method is homomorphic encryption, which encrypts data before it is sent to another party, allowing access to the overall results but not the raw data. For instance, if a company wants to survey students about their preferred model and colour of phone, it could collect the data and then share or sell the overall statistics, not the individual data points. However, this does not work when trying to export data to another country. Many countries have restrictions on data sharing, even when it is encrypted, which creates problems for multinational companies, academic researchers, or governments. For instance, if a firm has branches in Beijing, London and Hong Kong, it cannot easily share customer information. Moreover, there is always the risk that in 10 or 20 years, the encryption code will be broken. Professor Yiu and others in the field have been working on a workaround, which is federated learning. The raw data is processed in a model located close to the source and that model – not the data – is combined with models from other centres to give a close approximation of the overall results (Professor Edith CH Ngai is also working in this area, see page 10). Federated learning works well with non-sensitive uses such as marketing or promotions, but the technique is still imperfect. “It is more feasible because the data never goes out, but it may not be 100 per cent accurate,” Professor Yiu said. “It may also be possible to deduce the source of some of the data. For instance, if a company only has customers of a certain type in one country, and that group is included in their overall model, then that group becomes revealed.” Moreover, the user may need to recruit a third party to help develop a final global model, and there may be difficulties if too many different models need to be incorporated. A firm with dozens of branches across various countries will likely find the system too slow in combining input, versus a firm with only three branches.
HKU Bulletin | Nov 2025 Cover Story 6 7 No erasure Protecting one’s data through the consent process is also no guarantee that it is safe, he said. With privacy law. In Hong Kong, the Personal Data (Privacy) Ordinance dates to the 1990s but has not been updated despite such developments as AI and social media. “The law is so behind in technology, maybe decades behind. For the law to catch up now seems just impossible,” Dr Young said. Nonetheless, the law does provide some framework for privacy protection. Consent is important, although most people do not read the long passages in small font that pop up in consent boxes (not even Dr Young’s higher-level law students – he asked). It may also be very difficult to give consent, for instance, if self-driving vehicles use cameras to observe the street and identify objects and people. The vehicle may have passed by before you realise it has captured your image without your consent. How and why data is collected is also an issue, he said, particularly when there are breaches. Often, people do not know their data has been collected until they learn of the breach through the media or other sources. Even then, there is no legal obligation for firms in Hong Kong to report data breaches or compensate injured parties. In 2018, Cathay Pacific took months to report that hackers had accessed the personal details of 9.4 million passengers. Dr Young noted that technology itself can create vulnerabilities. For instance, when new systems are being integrated with old ones that lack the same security protocols, a malware or virus could use that vulnerability to worm into the system and steal data. the advent of AI and more sophisticated systems, it is possible to reconstitute a person’s identity from different sources – such as the IP address, apps used, photos and social media profiles – bypassing the need for consent. In fact, this data may have been collected legally in small, separate pieces that, alone, are not meant to be identifiers. “It is easy to combine this information if you have sophisticated AI because the cyber footprints are there,” he said. Getting oneself ‘erased’ from the internet is also no solution because while the information can be deleted on one platform, such as Google, it may still exist elsewhere in cyberspace. The one silver lining, Dr Young said, may be that cyberspace is de-institutionalised, making it very hard for a single institution to control everything. Still, most people, particularly young people, readily agree to share their data for free access to platforms (although Dr Young, who also trained as an economist, points out ‘nothing is free’). His students are also indifferent to the issue. While he now teaches three classes on privacy to meet demand, many tell him they find the issue boring. They are only studying privacy because law firms want that expertise. But they may be missing some of the bigger picture, he said. When privacy issues are combined with cybersecurity crimes, online safety and AI, it can lead to very real personal problems, such as health information leaks and cyberbullying. His advice for those concerned: keep important information offline and do not integrate devices and systems. “If it’s really that sensitive, put it on paper and lock it up,” he said. Dr Angus Young Thousands of people are losing money over scams all over the world. We are not talking about uneducated or particularly vulnerable people – professionals are affected, too. A lot of this starts with the loss of privacy. The prospect of having one’s personal information taken and used without consent has become an ever more urgent problem. Prior to the proliferation of computers, and later digital networks, such information could only be accessed in physical form. Now, with an internet connection and some savvy software, almost anyone can obtain personal, identifying details about someone from anywhere in the world. “The harm of having little to no privacy is that one loses one’s individuality, on the one hand. But on the other hand, it actually makes cybercrimes, such as scams and fraud, much easier,” said Dr Angus Young, Senior Lecturer in the Faculty of Law, who teaches postgraduate students about privacy and the law. Modern technology enables criminals to scrape personal information, such as photos or videos, from social media and other sources and use them to create deep fakes. In early 2024, for instance, a finance worker in a multinational firm in Hong Kong was tricked into believing they were on a video conference call with a senior member of the firm; the worker transferred HK$200 million to the fraudster. “Thousands of people are losing money over scams all over the world. We are not talking about uneducated or particularly vulnerable people – professionals are affected, too. A lot of this starts with the loss of privacy,” Dr Young said. Breaches of privacy in the digital age can open the door to cybercrimes. Dr Angus Young of the Faculty of Law considers the legal implications. When Privacy Is Threatened Way behind Unfortunately, laws to protect privacy are uneven across the world. The gold standard is the European Union’s General Data Protection Regulation, but enforcement is a challenge because of the huge resources required. In the US, only California has a
Letting consumers decide whether to share their data may not necessarily protect their privacy. It also gives mixed results to firms. Professor Xi Li has been investigating. A Catch-22 for Consumers HKU Bulletin | Nov 2025 Cover Story 8 9 Companies collect lots of data about their customers and try to use that to their benefit. 25 years ago, Amazon was discovered to be charging existing customers higher prices than new ones. Other firms soon followed suit. Orbitz, for instance, offers cheaper hotel options to Windows users than Mac users. Uber monitors customers’ battery levels and charges them more when batteries run low, on the presumption they cannot wait for a cheaper option. Outrage over these practices prompted governments to regulate data sharing, resulting in the European Union’s General Data Protection Regulation, China’s Personal Information Protection Law and other laws. But research by Professor Xi Li, a marketing expert in the HKU Business School, suggests such regulations may not always serve the best interests of consumers. For one thing, personalised pricing as described above is not all bad. While it can harm consumers under a monopoly, it benefits them when firms compete. Regulations also do not always perform as expected. “There are hundreds of regulations about who can use Sharing versus fraud One such instance is airline tickets – consumers may want to advertise on social media that they are not wealthy and cannot afford a ticket in the hope that a cheaper one is offered to them. The expectation is that the airline will see their post and act on it accordingly, which has happened on Chinese social media, he said. Another example is sharing your fitness data with an insurer, such as step counts, which can result in a lower premium offer because you are trying to stay healthy. There is an ongoing debate in China about the fairness of customising prices, but Professor Li found that in most cases, this can be useful because it enables more customers to use a service. However, there is a caveat for firms regarding consumer fraud to skew the data. He cited the example of a ‘phone cradle’ that rocks your phone to add to your step count even while you sleep. Consumers also use VPNs to hide their location because of price discrimination between such places as the US and less economically developed countries. “Our conclusion is that firm policies and government regulations on voluntary data sharing must be approached very carefully, otherwise they can backfire,” he said. “They must also take into account this manipulative behaviour. Consumers are not passive.” consumer data and how they can use it. The policies are much more complex than we expected, and they often have unintended consequences,” he said. For instance, while regulators have tried to establish that firms only collect data when consumers give consent, these same firms can still find out personal information about their customers without such permission. “For example, a firm will know who lives with you if you share the same address with people who opt to share their data, and it will assume you are all likely to be similar. The same is true of people in your social network. And just choosing not to share data can be revealing. In many of our models, we found that rich consumers do not want to share their data because they don’t want firms to know they are rich. But firms can then infer that they are rich. So they can exploit users regardless of whether they share data voluntarily,” he said. TL;DR (too long; didn’t read) Another problem is the terms and conditions of sharing. Many consumers automatically click ‘agree’ when asked to share, without reading the fine print, which is typically onerous to read. In 2019, The New York Times looked at the privacy policies of 150 popular websites and apps and found most took 10–20 minutes each to read and required a higher-than-tertiary-level education to understand. People will encounter several such policies every day through ordinary web searches. “We have found that consumers’ reluctance to read these statements can actually be detrimental to both consumers and firms,” Professor Li said. Consumers obviously risk having their collected data misused. But firms that try to do the right thing can lose out because consumers will not read their policies. This problem could be addressed by simplifying notices to a few lines and keeping consumers on that page for a few extra seconds so they will read them. Firms could also consider offering a reward to consumers who share their data. “That could improve profits without hurting consumers,” he said. Professor Li said the complexities of data sharing suggest that governments need to consider different ways of regulating it. They could make the decision for consumers in some instances, such as not allowing data sharing under a monopoly situation, while letting consumers take control when the outcome could be beneficial to them. Indeed, there are situations when consumers want companies to know more about them. Professor Xi Li There are hundreds of regulations about who can use consumer data and how they can use it. The policies are much more complex than we expected, and they often have unintended consequences.
‘The more data you have, the better the result’ is an idea that underpins AI and machine learning. By collecting huge amounts of data, it becomes possible to discern patterns and make accurate predictions or decisions. But that approach often fails to consider that the raw data usually belongs to an individual, revealing things that person may not want to share or even be aware of. Professor Edith CH Ngai of the Department of Electrical and Electronic Engineering has first-hand experience of this from her research projects, including a project on smart water auditing with the HKU Water Centre and the Water Supplies Department of the Government of the HKSAR to understand household water consumption patterns in Hong Kong. They affixed devices to water meters at homes to take photos Drawing on her experience collecting data that was more revealing than expected, Professor Edith CH Ngai has been working on ways to decentralise data collection and machine learning. A Better Way to Share of the readings, digitise them and report them to a central server. This enabled automatic and continuous monitoring of water usage to see when demand was high and when it abated. Surprisingly, it also revealed individual anomalies. One family was found to take long showers, another to use the washing machine several times a day, and still another to leave the kitchen tap running for long continuous periods. “Our original goal was to understand overall domestic water consumption in Hong Kong, but after investigating the data in detail, we found some weird behaviours that we didn’t expect,” she said. “As researchers, we want to understand the data of a certain community, but sometimes the data may also reveal things about individuals’ private lives.” HKU Bulletin | Nov 2025 Cover Story 10 11 A Smart Meter Analyser that can be clamped onto a government-issued water billing meter to digitise readings and automatically transmit the data to the cloud. Edge computing This relates to another area she is working on – edge general intelligence. ‘Edge’ means smart devices such as phones and computers that are handier and closer to the end users and can perform computations themselves, rather than sending data to a central server. Examples include Siri or AI personal assistants. This can also protect privacy, she said. Professor Ngai expects many more AI applications will be developed for smart devices. For university researchers, it is also a more fruitful path because they would not need large models and expensive computing power to conduct their studies. Professor Ngai admitted that while engineering scholars were less aware of privacy concerns in the past, possibly because the community uses many open-source datasets, awareness is increasing, as are more stringent ethical and privacy demands. This was reflected in her collaboration with the Faculty of Medicine on a study of children’s health before, during and after the COVID-19 pandemic. “Privacy demands are much more stringent for medical studies and journals,” she said. “A lot of people working on AI may still fight more for model accuracy and clean data. They do not want noisy or perturbed data. But as it gets closer to practical usage and applications by the general public, people will want more attention paid to privacy,” she said. Adding noise For instance, a person’s location may unknowingly be revealed when using apps. Professor Ngai cited the example of users who tag photos of animals or objects outdoors to aid machine learning. If their location can be determined, this would not only be of concern for the individual’s sake but may also deter others from providing data to improve machine learning models. “It’s a bit of a contradictory situation. If we get more data, then the model will be more accurate and powerful. But then the privacy concern becomes stronger,” she said. One solution is to add ‘noise’ to the data. For instance, a researcher monitoring physical activity could widen the monitoring area to incorporate dozens of people at a time, without pinpointing an individual and the paths they take every day. However, that risks sacrificing accuracy, she said. Professor Ngai has instead been looking at federated learning, which facilitates collaborative and distributed machine learning across different devices and users. Rather than sending raw data to a central server, individuals perform local training on their devices and send their updates of the model to the server, which combines input from all users without revealing private information such as users’ locations. “In this sense, people don’t need to share personal data, but they can still work together to do machine learning model training,” she said. Federated learning is still not perfect – malicious users may mislabel things to poison the model – so Professor Ngai is also working on ways to identify malicious updates and provide robust global aggregation. In this case, the families were not entirely unaware – they had been informed and given consent to the monitoring, and their data was securely stored and anonymised before data analysis. However, other data collection efforts may be less diligent or even less aware of the privacy threats. Professor Edith CH Ngai It’s a bit of a contradictory situation. If we get more data, then the model will be more accurate and powerful. But then the privacy concern becomes stronger.
Dried blood spot cards contain tiny blood samples from newborns that allow for early detection of disease. They also contain valuable information for medical research. But using the cards for research is not a given. Parents worry that if the cards are shared or acquired by third parties, the data could be used against the child in future, for instance, by being denied employment or insurance coverage. And who controls the data? What if parents change their minds? Similarly, the COVID-19 pandemic raised concerns about individual health privacy when people were asked to reveal personal information, such as their vaccination records and recent contacts. In both cases, public health could benefit from sharing the health information. Dr Olivia Ngan Miu-yung of HKUMed and Professor Jack Zhenhui Jiang, Padma Privacy, consent and governance concerns Dr Ngan interviewed parents and healthcare providers about the use, storage and sharing of dried blood spot cards and found that while parents were often willing to voluntarily have their children screened, tensions arose around sharing the cards for other purposes. There were worries about future genetic discrimination against their child and the possibility that parental consent could conflict with their children’s future wishes. Misuse is also a concern – in some places overseas, data has been used without consent. and Hari Harilela Professor in Strategic Information Management of the HKU Business School, have therefore each looked at the concerns and how to overcome them. Inducing social benefit feature Professor Jiang was interested in the conditions under which people are likely, or not, to share information. He set up two randomised experiments to study patient data donations relating to general medical research and COVID-19 and found participants were very reluctant to share sensitive information, such as details about blood tests, medicines taken, vaccinations and the like. “This kind of reluctance is having an impact. Several non-profit organisations overseas that collected people’s health data for research purposes have had to close because donations dropped,” he said. But he also looked at how to reverse that response and found, like Dr Ngan, that willingness to donate increases when people can control who accesses their data, can approve how it is used and can retract their donation at any time. Awareness of societal benefits also increased willingness to donate. When people were explicitly told their donation would benefit medicine or the community, they were more willing to donate. Similarly, if benefit was implied by including images of patients in hospital alongside the data donation request, they were also more willing to donate. Generic images of a landscape that were also used in the experiment had no such effect. “Every patient’s data is important, and we hope they can share their data. In general, if you give people proper privacy controls and you induce the idea of People understandably have privacy fears about sharing their medical data, even when others could benefit. HKU scholars have looked at how these concerns can be allayed while still protecting privacy. Giving for the Greater Good HKU Bulletin | Nov 2025 Cover Story 12 13 Sharing on social media Professor Jack Zhenhui Jiang has also looked at privacy and willingness to share in a social media context. In a frequently cited paper, he found people were more willing to share personal information if they were anonymous, but not if the other person was anonymous. Being asked too many questions about oneself decreased willingness, but communicating in a rich media environment, such as using video or voice rather than plain text, increased it. Some subjects simply opted to misrepresent themselves – tell lies – rather than opt out of sharing information. The study was done a decade ago and he now sees a minefield for privacy concerns given the ease with which people share their voices and images (and even those of their children) on social media and AI platforms. This information can now be easily manipulated, or at the least be used for AI training. “Privacy is a significant issue in the digital age, which is inevitable because information can be so easily shared, retrieved and misused,” he said. While Hong Kong has the Personal Data (Privacy) Ordinance, Dr Ngan said it is not explicit in preventing discrimination based on genetic data. “This framework may not fully address the unique risks associated with genetic information,” she said. One solution is to pseudonymise the data by storing identifiers separately from the samples and assigning a unique ID to the sample. Although this requires stringent data management protocols, parents were more willing to share information if it was pseudonymised, they were asked permission each time the data was used, and they had the right to withdraw the data at any time. “Hong Kong parents and healthcare professionals generally express positive attitudes toward using dried blood spot cards to advance research, but with varying degrees of concern about privacy, consent and longterm data governance. There is a pressing need for participatory research in this area,” she said. societal benefits, they will be more willing to share,” he said, adding the same could apply to other areas, such as requests to share diagnostic data from one’s phone or computer. Professor Jack Zhenhui Jiang This kind of reluctance is having an impact. Several nonprofit organisations overseas that collected people’s health data for research purposes have had to close because donations dropped.
With Flying Colours He sees SUPER being a gamechanger in several areas. Its ability to fly fast and safely in unknown environments makes it ideal for search and rescue, where it can quickly navigate disaster zones to locate survivors. In disaster relief, it could also deliver critical supplies through tricky terrains such as dense forests or urban ruins. “We’ve also tested it for tasks like tracking a moving person or vehicle, exploring unknown areas autonomously, and navigating preset waypoints, even in low-light conditions,” he said. “These capabilities open doors for applications in emergency response, environmental monitoring, or even logistics in challenging settings. Essentially, anywhere you need to operate autonomously in challenging environments.” The next steps for MAVs, including systems like SUPER, are about pushing the boundaries even further. The team want to make the drones even more robust so they can handle extreme weather, like heavy rain or wind, and navigate even denser environments. They are also looking to integrate advanced AI, such as machine learning for adaptive decision-making, as this could also help MAVs better predict and react to dynamic obstacles, like moving crowds or vehicles. “In addition, we’re looking at scaling this technology for broader applications, such as coordinating fleets of drones for large-scale tasks such as environmental mapping,” said Professor Zhang. “Ultimately, the goal is to make MAVs more autonomous, reliable, and versatile, so they become standard tools for industries and emergency services worldwide.” a drone to move quickly and reliably through complex spaces, SUPER can make a difference.” The team expect there to be strong interest from industry. “Achieving a 100 per cent success rate in tough tests and dodging obstacles as thin as power lines – has definitely caught people’s attention,” he said. “SUPER’s ability to outperform commercial drones in cluttered environments and handle diverse conditions makes it appealing for industries like logistics, as well as defence and emergency services. “We’re focussed on the research side, but the potential for realworld impact is clear, and I’d expect companies in these sectors to be very interested in how SUPER’s technology could enhance their operations.” Asked how he became involved in MAVs, Professor Zhang said: “I’ve always been fascinated by robotics and how we can push machines “This gives it two big advantages: first, it can move fast to reach destinations quickly, which is critical for things like disaster response. Second, it stays safe by using a smart planning system that always has a backup path to avoid collisions.” Lead author on the paper, which has been published by Science Robotics, is Dr Yunfan Ren, who commented: “SUPER is perfectly suited to achieving such dexterity partly because it is small – about 35 centimetres wide – and because it is equipped with a lightweight 3D light detection and ranging (LiDAR) sensor that acts like its eyes, spotting obstacles up to 70 metres away with pinpoint accuracy.” “Think of it as the drone constantly scanning its surroundings to build a 3D map,” said Professor Zhang. “It plans two paths every tenth of a second: a fast one that assumes unknown areas are safe to maximise speed, and a backup path that sticks to spaces it knows are obstaclefree to ensure safety. If something unexpected pops up, it switches to the safe path.” The breakthrough came from two innovations. First, the research team developed a new way to process LiDAR data directly, with what is called a point cloud map, which is 10 times faster than older methods because it is able to skip bulky computations. Second, they created a method called CIRI – configuration-space iterative regional inflation – that efficiently maps out safe regions while accounting for the drone’s size. “These let SUPER plan quickly and fly safely at high speeds, even in cluttered places like forests or at night,” said Professor Zhang. Fast and safe Game-changer SUPER’s ability to outperform commercial drones in cluttered environments and handle diverse conditions makes it appealing for industries like logistics, as well as defence and emergency services. Professor Fu Zhang “A combination of speed and safety is a game-changer because it makes drones practical for missions where every second counts, and it moves them from laboratory experiments to realworld tools,” said Professor Fu Zhang, who is Associate Professor of the Department of Mechanical Engineering, and Director of the University’s Mechatronics and Robotic Systems Laboratory. He and his team have pioneered research into Micro Air Vehicles (MAVs), integrating advanced sensing, planning and control to create systems like the safetyassured high-speed aerial robot (SUPER), which Professor Zhang described as the culmination of years of tackling tough engineering problems to make drones more capable and reliable. “Birds are incredible navigators,” he explained. “They zip through dense forests or crowded spaces at high speeds with almost no mistakes. We drew inspiration from that for SUPER because it’s exactly what we need for drones. By mimicking bird-like agility, SUPER can fly at speeds up to 20 metres per second – about 45 miles per hour – while dodging obstacles like trees or even wires just 2.5 millimetres thin.” Engineers have developed a drone capable of emulating bird flight – making it fast, safe and particularly suitable for situations where urgency is crucial. HKU Bulletin | Nov 2025 Research 14 15
Brain Waves on epilepsy-related research by building and testing multimodal large models,” said Professor Wong. Other new steps include extending the work to invasive neural recordings such as spike trains and electrocorticography, which could provide higher-quality signals for even better adaptation. They are also scaling up the memristor chip architectures and optimising the learning algorithms for faster convergence. Additionally, they are developing highly integrated memristor chips that combine neural signal acquisition, decoding and feedback in a single system. This integrated approach aims to comprehensively improve brain-computer interface performance and establish a stronger foundation for present and future applications. “We encoded 12 different flight commands including take-off, landing, hovering and directional movements along these four degrees of freedom,” said Dr Liu. “This represents a sophisticated control task that demonstrates the practical capability of our memristor-based BCI for complex real-world applications. The successful completion of a 3D flight trajectory around obstacles using only brain signals shows the precision and reliability our system can achieve in demanding control scenarios.” Throughout the sessions, the researchers monitored for errorrelated potentials to trigger coevolutional updates. They tracked both how the memristor decoder parameters evolved and how participants adapted their neural control strategies through multiple update cycles. The team are about to begin a collaboration with Queen Mary Hospital (QMH) to work on epilepsy data and are in the process of getting ethics approval from the Institutional Review Board, a joint body between HKU and the Hospital Authority. “Once this is cleared, we will discuss and collect in-house electroencephalogram datasets from QMH for potential clinical applications of our adaptive neural decoding technology. The collaboration would focus The work is significant in terms of assistive technologies and neurological rehabilitation because the co-evolutionary capability of the system directly addresses one of the biggest barriers to practical BCI deployment: signal drift and variability over time. In rehabilitation settings, where patients’ neural patterns change continuously during recovery, current systems require frequent manual recalibration by technicians. “Think of ‘co-evolution’ as like learning to dance with a partner,” explained Professor Wong, “Both dancers gradually learn each other’s style and adapt their movements to work better together. In our system, the human brain and the memristor decoder are like dance partners learning to collaborate.” “In technical terms, when the system makes a wrong decision, your brain automatically generates a detectable error signal called an error-related potential. Our memristor array monitors for these brain error signals. When detected, we apply small electrical pulses to the memristor hardware to change its resistance, which updates how the decoder interprets your brain patterns,” explained Dr Liu. “Meanwhile, you learn to adjust your mental control strategies based on the system’s feedback. Over time, both your brain and the hardware learn to work together more effectively. Our experiments show this creates an adaptive interaction where both sides contribute to improved orchestration,” explained Professor Wong. The system maintains performance autonomously through hardwarelevel adaptation, with experimental validation showing sustained accuracy over six-hour sessions and approximately 20 per cent improvement compared to static decoders. The ultra-low energy consumption enables extended daily usage without frequent battery replacement. “This could be transformative for patients requiring long-term neural monitoring or those using BCIs for daily assistance, as the system evolves with their changing neural patterns rather than becoming less effective over time,” said Professor Wong. To test the system, 10 healthy participants used brain signals to control drone movements in real time, each completing approximately six hours of testing across multiple sessions. These included controlling the drones at ‘four degrees of freedom’, which refers to the drone’s ability to move in four independent directions – forward and backward, left and right, up and down, and rotational (clockwise and counterclockwise spinning) – in a 3D space. Co-evolutionary capability Control scenarios The key innovation in this research is to showcase that memristor devices can accomplish real-time co-evolution between brain signals and hardware decoders. In simple terms, it is like creating a learning partnership where both the user’s brain and the memristor-based system adapt together, rather than forcing one to accommodate the other. This groundbreaking work represents a multi-institutional strategic collaboration between research teams at HKU, Tsinghua University and Tianjin University, with Professor Wong Ngai and Dr Zhengwu Liu serving as the lead contributors from HKU’s Department of Electrical and Electronic Engineering. “We leverage the memristor’s intrinsic plasticity to implement a co-evolutional process,” said Dr Liu. “When the brain generates error-related potentials following incorrect classifications, these signals trigger direct conductance changes in the memristor array, effectively updating the decoder parameters. Simultaneously, users gradually refine their neural control strategies based on system feedback.” Their approach further consolidates traditional multi-step decoding into single matrix operations, reducing computational complexity significantly while achieving much lower energy consumption compared to conventional CPU-based systems. “For memristor-based brain-computer interfaces (BCIs), this establishes a new paradigm where decoding hardware components serve as active learning partners rather than passive memory and computing elements, addressing the fundamental challenge of signal variability in neural interfaces,” said Professor Wong. Engineering researchers have implemented memristor-based neuromorphic decoders for brain-computer interfaces, creating a groundbreaking decoding system that can effectively co-evolve with changing brain signals. HKU Bulletin | Nov 2025 Research 16 17 This could be transformative for patients requiring long-term neural monitoring or those using braincomputer interfaces for daily assistance, as the system evolves with their changing neural patterns rather than becoming less effective over time. Professor Wong Ngai
The team, led by Professor Honglin Chen, developed the vaccine by utilising a live attenuated influenza virus (LAIV) vaccine platform – DelNS1 LAIV – which they originally developed in 2018. They first used the DelNS1 LAIV platform, which is designed for the development of influenza vector-based nasal spray vaccines, to guard against COVID-19 in 2020 when the pandemic was at its height. That vaccine was given approval in 2022 after completing three phases of clinical trials and was the first approved COVID-19 vaccine in nasal spray form. For this research, the DelNS1 LAIV platform enabled the scientists, who are from HKU’s State Key Laboratory of Emerging Infectious Diseases and the InnoHK Centre for Virology, Vaccinology and Therapeutics, to undertake the rapid development of the new nasal spray vaccine in collaboration with the Chinese Mainland’s Wantai BioPharm. Two key members of the team, Dr Pui Wang and Dr Shaofeng Deng, explained that while SARS-CoV-2 has gradually evolved into a seasonal respiratory virus, the chances of a similar virus emerging are inevitable – ‘Disease X’ as it is referred to in medical and scientific circles. The team chose to focus on a vaccine specifically for the H5N1 avian influenza virus as it has spawned multiple variants and is viewed as a highly likely candidate for triggering another human pandemic. Asked why they developed the vaccine as a nasal spray, Dr Deng said: “Intranasal vaccines work better than injections because they stop respiratory viruses like influenza right where they enter the body: the nose. While traditional shots mainly induce systemic immunity to fight the virus after infection (reducing severe illness but not blocking initial infection or spread), a nasal spray creates a frontline defence in the nasal mucosa. This triggers ‘mucosal immunity’, producing special antibodies (immunoglobulin A) that act like sticky traps in your nose, neutralising the virus on contact.” On the Nose Needle-free advantage “This not only prevents infection but also slashes the amount of virus you shed, making it far harder to spread to others. Add in the needle-free advantage – no pain or fear, especially helpful for kids and needleaverse groups – and you get a vaccine that blocks transmission and boosts real-world acceptance.” Implications for the vaccine are many, said Dr Wang: “As the findings in the paper demonstrate, our H5N1 DelNS1 LAIV is safe, immunogenic and can fully protect the upper (nasal) and lower respiratory tract (lung) in the two animal models – hamsters and mice – used for testing. Therefore, our vaccine provides good protection and can prevent transmission. “Also, the production yield is high, using an egg and cell culture system, which means the production cost is low and production can be scaled up easily.” Researching mucosal immunity is notoriously challenging, particularly when it comes to the generation of strong and long-lasting mucosal immunity. “We were trying to improve the antigen design to increase the immunogenicity of our vaccine,” said Dr Wang. “Also, due to our unique DelNS1 system, our vaccine can induce a strong innate immune response (interferon response). This serves as a natural adjuvant to strengthen the adaptive immune response. Another challenge with mucosal immunity is the safety issue. But our DelNS1 vaccine is very attenuated and had a very good safety profile in the clinical trials.” Should there be an H5N1 pandemic, the vaccine platform can serve as a valuable, rapid-response tool to be deployed immediately on a large scale if humanto-human transmission of a threat emerges. Dr Pui Wang Key innovations The team have also made significant improvements to the DelNS1-based receptor binding domain (RBD) LAIV vaccine design since the COVID-19 pandemic, Virologists have developed a nasal spray vaccine that is fast and effective against H5N1 in small animal models, and they are now set to start human trials. through two key innovations to enhance viral antigen expression and immunogenicity. “For the antigen design, we have used an immunefocussing approach,” said Dr Wang. “We added a glycosylation site to block the non-neutralising epitopes of the RBD and force the immune system to focus on the important receptor binding motif region. For antigen display, we added a transmembrane domain to the RBD antigen, so that the antigen would be expressed and displayed to the cell surface. This would greatly increase the immune response for the RBD antigen.” While they do not envision using the H5N1 vaccine as a general seasonal vaccine in the same way as annual influenza vaccines are now used, it could be used first as a preventative measure for high-risk groups. “Our vaccine can be used in affected areas, such as farms, for both humans and animals, to control any outbreaks,” said Dr Wang. “Should there be an H5N1 pandemic, the vaccine platform can serve as a valuable, rapid-response tool – leveraging its quick production capability – to be deployed immediately on a large scale if human-to-human transmission of a threat emerges.” For the future, Dr Deng also suggests wider applications. “This DelNS1 vaccine platform isn’t just for flu – it’s a plug-and-play system for respiratory viruses. Our next target is a multivalent vaccine: one spray for broader protection against flu, respiratory syncytial virus and COVID-19 at the same time. And to prepare for potential future pandemics caused by ‘Disease X’.” HKU Bulletin | Nov 2025 Research 18 19
Designer Genes Using resurrected 700-million-year-old genes, biomedical scientists have shown that molecular tools from ancient single-cell organisms older than animals themselves can transform animal cells into pluripotent stem cells, contributing to viable mice. HKU Bulletin | Nov 2025 Research 20 21 In so doing, the team have not only revealed the evolutionary origins of genes critical to stem cell biology but also overturned a long-held belief that such transformative capabilities are only found in animal genes. The team, which was led by Dr Ya Gao, Dr Daisylyn Senna Tan and Professor Ralf Jauch from the School of Biomedical Sciences at HKUMed, carried out the research in collaboration with Dr Alex de Mendoza of Queen Mary University of London, and Dr Mathias Girbig and Dr Georg Hochberg at the Max Planck Institute for Terrestrial Microbiology in Germany. “The most striking outcome of the research,” explained Professor Jauch, “is that when the protist SOX gene was used to create stem cells, they could successfully contribute to healthy mice despite hundreds of millions of years of independent evolution. The molecular tools we use to make stem cells have much deeper roots in our evolutionary past. “Stem cells are critical for multicelled life and can form all the hundreds of cell types of the animal body, and are essentially immortal as they can indefinitely propagate. It seems that nature used a pre-existing set of molecular tools and repurposed them rather than inventing new tools to make animal stem cells. “The research revealed that ancestral ‘Ur-SOX’ proteins which we predicted to exist in a ‘great-greatgreat-grandmother of all cells’ that we share with our unicellular relatives, can reprogramme mouse cells into pluripotent stem cells, challenging the belief that animal genes are unique and highlighting nature’s enduring ability to inspire innovation with a preexisting set of tools. It also shows that SOX and POU factors are older than stem cells and animals.” Our bodies consist of about 200 cells with special properties, each playing a critical role in maintaining overall health. “These are fit for their specialised job but cannot do the job of other cells,” explained Professor Jauch. “Pluripotent stem cells can make unlimited copies of themselves and can be nudged to form all of the 200 human cell types.” that normally regulates organ development — such as the gut and the liver — into a very powerful inducer of pluripotency with a single point mutation. “It has captivated me that we can drastically alter the function of molecules that parted ways, in evolutionary terms, hundreds of millions of years ago,” he said. “I want to know when and why these two molecules split up. This led me to travel back in time into our evolutionary past and to my surprise, I had to go much further back than I initially thought.” While the team’s work has largely concentrated on therapeutic medical applications, tangential uses are also possible, including the potential for preserving endangered species. “Preserving our genetic heritage is a mission of humanity – wildlife extinction is progressing at an alarming speed,” said Professor Jauch. “What we can do as biotechnologists is to preserve the stem cells of endangered animals. This will preserve their genetic blueprints within a living cell and could allow us to preserve critically endangered species such as the northern white rhino, even restore a species that we lost, such as the dire wolf. “Yet, for most animals we are currently not able to make stem cells. Enhanced and re-designed factors optimised based on evolutionary principles can help democratise stem cell generation across animals.” Endangered species The work paves the way for new protein designs in novel therapies for regenerative medicine and disease studies to combat health issues related to ageing. Custom-designed proteins are already used in the healthcare industry to turn regular cells into stem cells for therapeutic applications, and currently the field is developing ChatGPT for protein to design purpose-built proteins for biomedical applications. “These algorithms stand on the shoulders of natural evolution and the beauty of life,” said Professor Jauch. “We expect our findings will further help train AI algorithms to optimise molecules that we can use to engineer the properties of cells to study diseases in the laboratory, to regenerate damaged tissues with newly-made cells and even to reverse ageing.” This translational work will be driven by Dr Gao and Dr Tan, co-first authors of the study, at HKU’s Centre for Translational Stem Cell Biology at the Hong Kong Science and Technology Park. “We can use designer genes to transform blood into mature neural cells, which can help us understand what goes wrong when neurons degenerate and neurological diseases develop.” Professor Jauch’s interest in ancient proteins began years ago with the discovery that he could turn a gene Novel protein designs From left: Dr Daisylyn Senna Tan, Dr Ya Gao, Professor Ralf Jauch, and Dr Alex de Mendoza. It seems that nature used a pre-existing set of molecular tools and repurposed them rather than inventing new tools to make animal stem cells. Professor Ralf Jauch
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