The 'black box' of nursing talent’s ebb and flow

Singapore Management University

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SMU Associate Professor Yasmin Ortiga undertakes novel study of state policies’ influence on Filipino migrant nurses’ global movements.

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Credit: Singapore Management University

SMU Office of Research Governance & Administration – Associate Professor Yasmin Ortiga chats with Filipino nurses for a living. The sociologist at Singapore Management University (SMU) tends to ask them about their hopes and dreams, why they uprooted themselves to go work in a hospital miles away from their home in the Philippines, often leaving young children behind. Every conversation builds up her research on international migration. 

Of late, the chats have thrown up cases of these migrant nurses choosing to bypass Singapore, which relies on Filipinos for over half of its foreign registered nurses. A blip or a notable shift in migration patterns? That is one of the questions Professor Ortiga seeks to answer in her latest research, “Tracing Nurse Trajectories: Multinational Migration Amid Global Competition”. 

The proposal, which has received a Ministry of Education (MOE) Academic Research Fund (AcRF) Tier 2 grant, will be the first to quantitatively trace the diverse global pathways of migrant nurses, providing information such as time spent in each place, in relation to factors including age and social class.

“We know there is major competition for nurses. This project is basically about proving empirically that this competition has a way of moving nurses towards one place and keeping them away from others,” Professor Ortiga told SMU’s Office of Research Governance & Administration (ORGA) in an interview.

Illuminating the “middle space”

Steering away from conventional thinking in migration studies that an individual moves for personal reasons to a foreign place, her project will consider myriad external factors as well as the concept of some places being “stepping stones” before the individual settles down in a desired destination. This so-called “middle space” is what Professor Ortiga will scrutinise.

“Often, there’s this black box in the middle. For a long time, scholars didn’t try to understand how people move across borders, who handles their paperwork, and who gave them the idea to move to this place rather than another. Now, we know that there is a middle space of recruiters, brokers, state officials and other migrants who also influence that decision,” she explained. 

“We’ve never really recognised this middle space in terms of how it shapes migration patterns. There has been more research on brokers in recent years, but even then, a lot of the focus has been on how brokers move people from Point A to Point B, it’s always a single origin and a single destination.”

The reality, she said, is “a global marketplace, where everyone is competing for the same pool of labour”.

Mixed-method research for new knowledge

This three-year project will produce new data to enrich migration studies. 

To capture Filipino migrant nurses’ actual movements across borders alongside significant policy changes, Professor Ortiga will use the Event History Calendar, a survey instrument that allows researchers to reconstruct significant events in a respondent’s life history. The target is to survey around 2,400 Filipino nurses who have either worked or are currently working in Singapore – an established stepping-stone destination – and the United Kingdom (UK), a “desired” end-destination known to offer higher wages and the possibility of permanent residency. Comparing these two pathways will enable the project team to determine how changes in a desired destination affects nurse trajectories towards another.

To investigate how actors within the “middle space of migration” work, the team will conduct in-depth interviews with 50 state officials, brokers, hospital administrators, and nursing school owners, all from Singapore, the Philippines and the UK. This will shed light on the kinds of strategies formulated and implemented in a bid to influence nurses’ career decisions.

For insight into the nurses’ perspectives, the team will use the “digital story completion method”, a popular approach in the medical humanities. Around 100 nurses, who are either working in or had passed through Singapore, will go online to read the beginning of a hypothetical scenario or so-called “story stem”, and then complete the story in their own words by typing in their responses. The project team will then analyse the completed stories to see how nurses’ responses change when variables change. 

This will mark the first time that the digital story completion method is being implemented in Singapore, having enjoyed success in other research sites, said Professor Ortiga.

Impact on stepping-stone countries like Singapore

Professor Ortiga believes the project will help policymakers who are facing growing competition for the migrants they need to meet their population’s burgeoning demand for healthcare workers. Singapore is a prime example: Not only does it have to fend off other “stepping stones” – such as Kuwait and Japan – for migrant nurses, it is also feeling the heat from desired destinations that have started relaxing their formerly-stringent criteria. So there is a fight for numbers, as well as for the crème de la crème.

“If you look at the numbers, Singapore is still able to recruit nurses from the Philippines, but my question is, ‘Who is coming?’ My hunch is, it’s not the best nurses,” said Professor Ortiga. “The most experienced nurses that come from the Philippines’ best nursing schools – they are the ones more likely to skip to their desired destination.”

One strategy is to craft state policies and programmes geared towards attracting overseas nursing talent, she said. Another is for Singapore to play to its advantage of proximity.

“What I hear from my interviewees is that it’s very hard to get time off as a nurse in Singapore: Very heavy workload, stressful job. So some of them do wonder, what’s the point of being so close if I don’t get to fly home anyway; I might as well work in Saudi Arabia, where they give me free housing, or go straight to the UK.” In short, offer work-life balance to the migrant nurse, too, says the sociologist with her ear firmly to the ground.

 

Robots that rethink: A SMU project on self-adaptive embodied AI

Singapore Management University

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SMU Assistant Professor Zhu Bin is leading research to build embodied AI systems that adapt their actions when the world around them changes.

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Credit: Singapore Management University

By Vince Chong

SMU Office of Research Governance & Administration – It might not be ubiquitous just yet but embodied artificial intelligence is slowly but surely cementing its place in the world. Robotic systems equipped with sensors and cameras help with everything from factory assembly to surgery, while autonomous, self-driving cars and drones are science fiction no more.

Despite these advances though, there is a limit to what embodied AI can do in unpredictable, everyday environments like homes or offices. Say, a robotic arm may be programmed within perimeters to make a cup of coffee. But hide the cup in a nearby cupboard and the task breaks down. 

It is “simple but frustrating” observations like these that sparked one of SMU Assistant Professor of Computer Science Zhu Bin’s latest projects, which won an Academic Research Fund (AcRF) Tier 2 grant from the Singapore Ministry of Education (MOE).

“In the area of embodied AI, robots could execute a fixed script perfectly. But the moment something changed, like a cup being misplaced, even the most advanced robot may fail [since it’s not in the coded script],” he told the Office of Research Governance & Administration (ORGA). 

“[Filling] that gap between static intelligence and adaptive reasoning inspired this project.” 

The award-winning research Self-Adaptive Planning with Environmental Awareness for Embodied Agents lays the foundation for the next generation of adaptive embodied systems, the computer science expert said, referring to AI “that can reason about why and how to act, not just what to do.” 

This could then be applied successfully to elder care to help with complex, multi-stepped tasks such as meal preparation, medication reminders, and light household chores. Or in healthcare, where they could be put more effectively to work as rehabilitation or therapy companions to track a patient’s movements and adapting exercises based on fatigue or recovery progress.

This is particularly salient in Singapore where elder care and healthcare are “critical” concerns due to its ageing population, the research notes. It adds that such innovations can help drive “socially responsible advancements while contributing to Singapore’s vision of becoming a global leader in AI and smart technologies.”

“In practical terms, the potential applications are broad and socially meaningful,” Professor Zhu said. 

The project is led by Professor Zhu and involves Assistant Professor Kotaro Hara, also of the School of Computing and Information Systems, SMU, as well as Franklin Li Mingzhe, a doctoral candidate, and Associate Professor Patrick Carrington, both of the Human-Computer Interaction Institute at Carnegie Mellon University in the US. 

Gruelling AI training

At its core, the project tackles three key problems in embodied AI’s current form, Professor Zhu explained.

Firstly, many current systems rely too heavily on large language models (LLMs) trained on general world knowledge, which can lead to “unrealistic or irrelevant plans”. Examples of LLMs include AI-powered applications such as ChatGPT and DeepSeek that are designed to understand and produce human-like text. 

Secondly, the research notes, embodied AI, as it is, lacks awareness of environmental changes, and is hence unable to track surrounding changes, even small ones. Lastly, it is inflexible and incapable of adapting to elements that are out of place vis-à-vis its coded blueprint. 

The project aims to resolve these issues through, among other things, vigorous and detailed training. This includes feeding its AI software with roughly 200 distinct kitchen tasks in video form, each repeated about 300 times. 

In total, the system will analyse and learn from some 60,000 high-quality video sequences aimed at tracking all potential changes in the task environment. As the project notes, existing work in video understanding “often neglects the complexities of tracking objects … in dynamic, interactive environments.”

“By incorporating first-person perspectives and real-time object state tracking, [the project] will provide new insights into building embodied AI systems,” it states.

The project also plans to develop a LLM to allow an embodied agent to refine tasks on the fly based on real-time feedback. In other words, it allows the robot to learn from what it sees and senses to refine its next move on the spot, rather than rigidly following a preset script. This, Professor Zhu added, makes the agent “more flexible, reliable, and responsive in everyday situations.”

Hence, using the earlier coffee-making example, if a robot is unable to find a mug in the expected location, it may then infer through its LLM that mugs are typically stored in cupboards. It will then update its task plan to include new subgoals such as "open cupboard" and "search for mug" before making that cup of coffee. 

As the research notes, the “success of this project could reshape the research landscape in embodied agents.”

Modular, plug-and-play approach

Not surprisingly, Professor Zhu said, his team’s research will be designed in a way that can be directly integrated with future adaptive AI models. This is to avoid falling behind the curve given the rapid pace of technological development.

“Our focus is on general and transferable algorithms, not on a single model snapshot,” he said.

“Rather than competing with every new model, we will design our framework to be modular and plug-and-play. That’s how we remain relevant and resilient in a fast-moving field.”

The academic is also sanguine about the risk of AI misbehaving or going rogue, a concern that has emerged lately among experts. Is he at all worried, particularly with using embodied agents to help physically weaker demographics such as the elderly and infirmed?

Safety, he said, is always a key consideration in any project that “aims to move embodied AI systems towards deployment in the physical world.” The best methods to mitigate concerns are “through human-in-the-loop supervision, rule-based constraints, and extensive real-world testing” before any deployment in sensitive contexts like elder care or healthcare. 

“These ensure that embodied agents act within well-defined boundaries and always under human oversight,” Professor Zhu said.

“Ultimately, the goal is to develop empathetic, environment-aware AI assistants that complement human care and promote safer, more independent living.”

 

SMU and South Korea to create seminal AI deepfake detection tool

Singapore Management University

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SMU Associate Professor He Shengfeng is working on the first-ever multilingual system suitable for Asia, with commercialisation prospects.

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Credit: Singapore Management University

SMU Office of Research Governance & Administration – In a coup for Singapore Management University (SMU), a team led by Associate Professor of Computer Science He Shengfeng has edged out competing research institutions to clinch a grant for developing a groundbreaking deepfake detection system.

The Artificial Intelligence (AI) project, when completed in an estimated three years’ time, promises to have widespread commercial applications. It would also be the first multilingual deepfake data set that includes dialectal variants such as Singlish and Korean dialects.

“Many existing tools don’t perform well on Asian languages, accents, or content,” Professor He told SMU’s Office of Research Governance & Administration (ORGA) in an email interview. “We’re focused on building something that fits the specific needs of our region.”

A detection tool that understands different linguistic, socio-cultural and environmental characteristics was a key requirement in the grant call issued in March 2025 by AI Singapore (AISG) and South Korea’s Institute for Information & Communication Technology Planning & Evaluation (IITP). AISG is a Singapore Government-wide initiative with several coordinating agencies. Under the grant, a bilateral research team would produce a tool suited to Singaporean and South Korean contexts.

SMU’s partner is Sungkyunkwan University (SKKU) whose Principal Investigator is Associate Professor Doowon Jeong. The collaboration is one that creates “a strategic attack and defense loop”, said Professor He, whereby the Singapore side focuses on creating and spotting fake videos, while the South Koreans zoom in on whether a video is real and on tracing its history.

“So we’re building a cycle where one team learns to make and detect, and the other strengthens the tools to verify and protect. It’s like testing and improving a security system by acting as both the attacker and defender,” Professor He explained.

How DeepShield will break new ground

The team has named their proposed system DeepShield, which aims to make several breakthroughs in the global race to combat realistic fake media that have been used to spread misinformation, fraud and identify theft.

“Unlike prior work narrowly focused on facial deepfakes, we introduce the first unified interpretable detection system capable of handling diverse and multi-modal manipulations – including object insertions, lighting alterations, background swaps, and voice dubbing – within a single, explainable pipeline,” according to their proposal paper.

Second, the team plans to create the first invertible embedding framework for video forensics, embedding invisible yet reversible signatures into edited content. “This enables not only tamper detection but full content restoration without extra storage – offering a breakthrough in traceable AI-generated media and digital provenance,” said Professor He.

Third, the system will be “inherently localised”, supporting dialect-aware detection tailored for deployment in culturally diverse regions like Singapore and Korea. This ensures that detection is not biased toward English or Western content, the team said in a video presentation of their proposal.

Overall, DeepShield aims to position itself as “not merely a detection tool, but a next-generation AI governance layer for digital media integrity – setting it apart from commercial offerings in both ambition and design”.

Work commences in January 2026. The team will begin scouring large-scale, publicly available datasets such as the YouTube8M dataset, which contain videos that are non-personal, diverse in content and widely used in academic research. They target to collect around 200,000 annotated video clips, which will be screened by AI tools as well as human staff who will verify samples for clarity, relevance, and public appropriateness, said Professor He.

As for deepfake versions, he added, they will be generated by the researchers themselves to enable full control over what was modified and to allow accurate annotation. “This setup allows us to scale data collection while maintaining transparency and quality control,” he said.

Roping in industry big names

Crucial to success is the involvement of industry players in the development and testing phases. 

One is Singapore-based Ensign InfoSecurity, the largest cybersecurity service provider in Asia, which will support a testbed simulating telecom and public sector video stream screening. In South Korea, SKKU will collaborate with Deepbrain AI, a generative AI company that specialises in hyper-realistic AI avatars, to evaluate the system in a cloud-based setting for enterprise media applications. 

Their combined involvement “ensures our system is tested in high-traffic, user-facing platforms particularly for news verification and short-form video integrity”, said the bilateral team.

If all proceeds smoothly, the team envisions “a start-up spin-off that would offer services such as deepfake forensics, media authenticity verification, enterprise compliance, digital governance platforms”. In addition, they said, there may be licensing opportunities to governments, banks, media platforms such as TikTok and Tencent, and AI auditing agencies across Asia.

The ambitious project is “more complex” than anything he has attempted, said Professor He, who was named in 2023 and 2024 among the world’s top two-percent most-cited scientists using citation metrics (excluding self-cites) in the annual lists compiled by Stanford University and Elsevier.

“We’re not just building a new algorithm in the lab,” he said. “We’re working across countries, cultures, and languages, and involving both academic teams and companies. We have to think about data collection, system design, real-world testing, and even policy implications. That makes it more demanding, but also more meaningful.”

UH, OH

Africa’s forests have switched from absorbing to emitting carbon, new study finds

Analysis led by University of Leicester shows the African continent lost approximately 106 billion kilograms of forest biomass per year between 2010 and 2017

University of Leicester

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Professor Heiko Balzter, Dr Nezha Acil (right) and University of Leicester colleagues at a zoobotanical garden at the Museu Emilio Goeldi in Belém, with trees and animals from the Amazon.

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Credit: University of Leicester

Groundbreaking new research warns that Africa’s forests, once vital allies in the fight against climate change, have turned from a carbon sink into a carbon source.

A new international study published in Scientific Reports and led by researchers at the National Centre for Earth Observation at the Universities of Leicester, Sheffield and Edinburgh reveals that Africa’s forests, which have long absorbed carbon dioxide from the atmosphere, are now releasing more carbon than they remove.

This alarming shift, which happened after 2010, underscores the urgent need for stronger global action to protect forests, a major focus of the COP30 Climate Summit that concluded last week in Brazil.

Using advanced satellite data and machine learning, the researchers tracked more than a decade of changes in aboveground forest biomass, the amount of carbon stored in trees and woody vegetation. They found that while Africa gained carbon between 2007 and 2010, widespread forest loss in tropical rainforests has since tipped the balance.

Between 2010 and 2017, the continent lost approximately 106 billion kilograms of forest biomass per year. That is equivalent to the weight of about 106 million cars. The losses are concentrated in tropical moist broadleaf forests in countries such as the Democratic Republic of Congo, Madagascar, and parts of West Africa, driven by deforestation and forest degradation. Gains in savanna regions due to shrub growth have not been enough to offset the losses.

Professor Heiko Balzter, senior author and Director of the Institute for Environmental Futures at the University of Leicester, said: “This is a critical wake-up call for global climate policy. If Africa’s forests are no longer absorbing carbon, it means other regions and the world as a whole will need to cut greenhouse gas emissions even more deeply to stay within the 2°C goal of the Paris Agreement and avoid catastrophic climate change. Climate finance for the Tropical Forests Forever Facility must be scaled up quickly to put an end to global deforestation for good.”

The research draws on data from NASA’s spaceborne laser instrument called GEDI and Japan’s ALOS radar satellites, combined with machine learning and thousands of on-the-ground forest measurements. The result is the most detailed map to date of biomass changes across the African continent, covering a decade, at a resolution fine enough to capture local deforestation patterns.

The findings come as the COP30 Presidency announced the new Tropical Forests Forever Facility, which aims to mobilise billions of Pounds for climate finance. It would pay forested countries to leave their tropical forests untouched.  The results show that without urgent action to stop forest loss, the world risks losing one of its most important natural carbon buffers.

Dr Nezha Acil, co-author from the National Centre for Earth Observation at the University of Leicester’s Institute for Environmental Futures, said: “Stronger forest governance, enforcement against illegal logging, and large-scale restoration programs such as AFR100, which aims to restore 100 million hectares of African landscapes by 2030, can make a huge difference in reversing the damage done.”

Dr Pedro Rodríguez-Veiga, who carried out the bulk of the analysis at NCEO and University of Leicester and now working at Sylvera Ltd., said: “This study provides critical risk data for Sylvera and the wider voluntary carbon market (VCM), and shows that deforestation isn’t just a local or regional issue — it’s changing the global carbon balance. If Africa’s forests turn into a lasting carbon source, global climate goals will become much harder to achieve. Governments, the private sector, and NGOs must collaborate to fund and support initiatives that protect and enhance our forests.”

The work was supported with public investment by the UK Natural Environment Research Council (NERC), the European Space Agency (ESA), and partner institutions across Europe and Africa.

• The study, “Loss of tropical moist broadleaf forest has turned Africa’s forests from a carbon sink into a source,” was conducted by an international team from the University of Leicester, University of Sheffield, University of Helsinki, University of Edinburgh, Wageningen University & Research, GFZ Potsdam, Sylvera Ltd and other institutions. DOI: 10.1038/s41598-025-27462-3 Link: https://www.nature.com/articles/s41598-025-27462-3 (to go live after embargo lifts)
• Tropical Forests Forever Facility: https://tfff.earth/

Professor Heiko Balzter and Dr Nezha Acil at the COP30 Climate Summit in Belém, Brazil.

Credit

University of Leicester

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Journal

Scientific Reports

DOI

10.1038/s41598-025-27462-3 

Article Title

Loss of tropical moist broadleaf forest has turned Africa’s forests from a carbon sink into a source

Article Publication Date

28-Nov-2025