Lessons from Singapore: What Can the Hungarian Research System Learn from Singapore’s Vibrant Research and Innovation Ecosystem?

Heng Swee Keat, Chairman of Singapore’s National Research Foundation (NRF), visited Budapest in May 2026 at the invitation of Hungarian partners and delivered the opening address at AI Symposium 2026, the international conference jointly organized by HUN-REN and Nanyang Technological University (NTU). In his speech, he described artificial intelligence as a general-purpose technology whose benefits will depend not only on technical capability, but also on scientific depth, institutional responsibility and trusted international cooperation. He also emphasized three broader lessons that resonate throughout the interview you can read below: strong research ecosystems are built over time; AI increases rather than reduces the value of international collaboration; and continuity matters during periods of technological and geopolitical change.

The NRF occupies a central place in Singapore’s national research and innovation architecture. It is not simply a funding agency, but a strategic institution that helps define national priorities, coordinate long-term public investment, connect research excellence with economic and societal goals, and build the capabilities required for future growth. In his Budapest address, Heng noted that under the RIE2030 plan, launched in December 2025, the country has committed S$37 billion (EUR25 billion or HUF8.900 billion) over five years to research, innovation and enterprise, with roughly one third allocated to basic research and substantial emphasis placed on AI, talent development and international partnerships. In that sense, the NRF is one of the principal instruments through which Singapore turns long-range state strategy into research capacity, innovation policy and international scientific engagement.

His Budapest programme reflected precisely these themes. In addition to his keynote speech at the AI Symposium, he visited major Hungarian research, university and innovation institutions, as well as leading companies, where discussions focused on R&D governance, research funding structures, AI and digitalization, engineering education, translational science, pharmaceutical innovation, industrial cooperation, startup ecosystems, talent development and internationalization. Potential areas for future cooperation that emerged included AI, health and biomedical research, pharmaceutical R&D, sustainability, water, energy, advanced manufacturing, postgraduate training and broader researcher exchange.

A notable moment during the visit was the signing of a new memorandum of understanding between NTU and HUN-REN at AI Symposium 2026. Building on the earlier agreement concluded in October 2024, the new MoU provides a framework for continued and expanded cooperation between NTU's College of Computing and Data Science and HUN-REN. Its substantive focus includes joint research activities, the possible establishment of joint PhD scholarship and seed-grant schemes, and the exploration of a more specific future research collaboration agreement.

Several key ideas from Chairman Heng’s Budapest speech reappear in the interview that follows. He stressed that research ecosystems cannot be built overnight, and that durable scientific cooperation depends on repeated exchanges, institutional continuity and investment in people. He also suggested that, in an age of fast-moving technologies, countries and institutions will gain advantage not only from computational scale, but from their ability to connect disciplines, researchers and international partners effectively. These are also central themes in his reflections on Singapore’s own system: long-term planning combined with strategic flexibility, strong support for fundamental science, investment in talent, evidence-based policymaking and a deliberate effort to align research with broader national priorities.

At a time when Hungary is debating questions of institutional reform, competitiveness, funding structures, scientific autonomy and the relationship between research and national development, the Singaporean experience does not offer a simple template. It does, however, offer a set of serious lessons — about continuity, coordination, public trust, talent and the conditions under which scientific excellence can be translated into long-term national capability. 

Q: Singapore’s research, innovation and enterprise system is built around multi-year national plans and unusually stable public commitment. What makes that long-term model work, and which elements could other countries realistically adapt?

A: Every country has its own institutional culture, but there are a few principles that matter everywhere. The first is political commitment. In Singapore, support for research, science, technology and innovation has been consistent across generations of leadership, from our founding prime minister to the present day. That continuity matters because research only delivers over time.

The second is public understanding. We have invested heavily in education and in building respect for science and mathematics. Singapore is a small country with real structural constraints, so science, technology and innovation are not optional for us; they are central to our survival and success.

The third is accountability. Long-term commitment does not mean writing blank cheques. People must see that public investment is taken seriously and that the system is expected to produce results, even if some of those results take many years to emerge.

Q: That raises an obvious question: how do you sustain political and social support when the most important results may take years to appear?

A: You begin by being honest about the nature of research. Not every field will produce visible results quickly, and not every project will succeed. There will be breakthroughs and there will be failures. That is the reality.

At the same time, governments have to make the case that some capabilities can only be built through patient, sustained investment. Singapore has been investing in science and technology for more than 30 years. We keep learning, refining and improving, but the underlying commitment has remained stable.

What also helps is an evidence-based approach to policymaking. In the end, the question is whether something works. If people can see that science-based decisions improve resilience, strengthen the economy and help solve real problems, support becomes easier to sustain.

COVID was a very important example. Because we had already invested for years in areas such as genetics and mRNA-related research, we were in a better position to respond. We relied on scientific expertise to understand how the virus spread, what precautions were necessary and how to protect the population. Public trust in institutions and in scientists mattered greatly, and so did the willingness of scientists to explain the facts clearly. That experience reinforced confidence in research and in evidence-based policy.

Q: So the need for economic impact does not come at the expense of basic science?

A: Not at all. We have been consistently supportive of fundamental science. In fact, about one third of our research budget goes to basic research through competitive processes, much of it investigator-led and bottom-up. That is important not only because fundamental science matters in its own right, but because universities need intellectual freedom if they are to remain excellent and train strong students.

At the same time, we are realistic about our size. Singapore’s R&D spending is significant for us, but small in global terms. That is why international partnerships are so important. A small country has to be very deliberate in choosing where it builds depth and where it connects to the wider world.

Q: How do you preserve that long-term direction while staying flexible enough to react to disruptions such as generative AI?

A: We try to build flexibility into the system rather than treat it as an exception. Our research planning runs in five-year cycles, but we know that technologies can move much faster than that. So we always set aside part of the budget as what we call “white space” — resources that are not fully committed from the start and can be deployed when new priorities emerge.

We also review our plans in the middle of the cycle. A long-term plan should provide direction, but it cannot be rigid. If a new field becomes strategically important, we need room to move. Equally, if an area performs better than expected, we may decide to reinforce it.

What matters is not constant disruption, but structured adaptability. You need enough stability to build capability, and enough flexibility to respond when the world changes.

Q: Does that mean weaker-performing projects are cut early?

A: Not automatically. Research does not always move in a straight line, so the issue is not simply whether something produces immediate results. The more important point is that part of our funding remains uncommitted, which gives us room both to back emerging opportunities and to scale up areas that are proving especially promising.

In universities, that is complemented by support for smaller, investigator-led projects. Good ideas often emerge from the bottom up. If they show real promise, we can then expand support. So the system tries to combine strategic direction with room for discovery.

Q: If a country wants to strengthen its innovation ecosystem, how should it think about the balance between excellent basic research and more mission-oriented programmes with nearer-term economic or social impact?

A: It has to be a portfolio. Basic research is essential because it creates capability, develops people and opens up future possibilities that cannot always be predicted in advance. At the same time, governments also need mechanisms that connect research to economic transformation and societal needs.

In Singapore, we have tried to do both. The research strategy is deliberately linked to enterprise and innovation, not just academic excellence. That means working closely with industry, thinking about technology adoption and ensuring that firms have pathways to transform themselves.

A good example was our Future Economy work. We developed industry transformation plans sector by sector, covering most of the economy. These plans combined four things: changes in business strategy, especially through technology adoption; operational redesign; workforce reskilling; and internationalisation. We worked closely not just with companies, but also with trade unions and the education system.

That broader coordination matters. Innovation policy is not just about funding laboratories. It is also about helping firms adopt technology, helping workers adapt and helping whole sectors move up the value chain. In the years after implementation, we saw strong productivity growth, which helped validate that approach.

Q: That points to another Singaporean strength: the ability to connect universities, research institutes and industry. In practical terms, how do you prevent those actors from operating in silos?

A: Incentives matter. If researchers from different universities work together on a project, that improves their chances for funding. We also encourage institutions not to duplicate one another unnecessarily. If one university has real strength in one area and another has strength elsewhere, they should collaborate rather than replicate.

More broadly, we place a lot of emphasis on multidisciplinary and interdisciplinary work. Increasingly, the most important problems do not fit neatly within one discipline or one institution. So the question should not be: who owns this problem? The question should be: what impact are we trying to achieve, and who needs to be involved to achieve it faster and better?

That logic applies internationally as well. For a country like Singapore, collaboration across borders is not supplementary; it is essential.

Q: When a breakthrough technology appears, what does rapid response actually look like inside the system?

A: It helps to have a government structure that is used to working across ministries and making decisions quickly. When I was in cabinet, we met every week, and there were many formal and informal mechanisms for coordinating across agencies. If a technology is judged likely to have major national impact, ministers can elevate it quickly and mobilise the relevant parts of government.

The second requirement is fiscal and institutional room to act. In research funding, that means keeping some flexibility inside the system. In government budgeting more broadly, it means maintaining buffers and reserves so that you are not paralysed when something unexpected happens.

AI is a good example. Once it was clear that it would have broad strategic implications, it became a national priority. We developed the National AI Strategy, implemented it, learned from experience and then updated it. The same logic applies in other emerging areas, including quantum technologies, where earlier investments are now beginning to yield real capability.

Q: If you were advising other countries on the highest-leverage steps they could take over the next few years to strengthen the links between public research, higher education and innovation-driven industry, what would you prioritise?

A: First, establish credible long-term direction. Researchers, PhD students, universities and companies all make decisions over long time horizons. If government priorities change abruptly and unpredictably, the whole system becomes hesitant. Stability does not mean never changing course, but it does mean that change should be thoughtful and strategic, not impulsive.

Second, build a culture of collaboration at home and abroad. In too many systems, researchers in the same country — sometimes even in the same institution — do not know what others are doing. That is a missed opportunity. Collaboration is how capabilities deepen, how duplication is reduced and how better ideas emerge.

This symposium is itself a good example. During the coffee break I spoke with several researchers and found that quite a lot of collaboration was already taking place — while others were discovering one another's work for the first time and immediately asking how they might work together. The memorandum of understanding signed between NTU and HUN-REN reflects the same spirit. I also spoke with Prof. Philip Chiu from the Chinese University of Hong Kong who had shown a slide about collaboration with both NTU and NUS. When I asked how he had first come to know the colleagues involved, he said he had spent time in Singapore ten years ago — a reminder that relationships formed early can become the foundation for serious collaboration years later.

That is why exchanges matter so much, especially for younger researchers. Many long-term partnerships begin with people simply getting to know each other early in their careers. Once those relationships are formed, they often become the basis for future collaboration across institutions and countries.

Q: Talent is clearly central to all of this. How do you attract and retain top researchers?

A: You have to build your own pipeline, and you also have to remain open to the world. Singapore began investing in talent systematically many years ago through scholarship schemes that support outstanding students from undergraduate study through postgraduate training. That has created a strong base of researchers who returned and now contribute across universities, research institutes and industry.

At the same time, we have benefited enormously from global talent and from distinguished scientists who came to Singapore and helped mentor younger researchers. In fact, Professor Gulyás presented me here with a bronze portrait of Sydney Brenner — a Nobel laureate who spent many years in Singapore and whose influence on our biomedical research community was profound. He mentored many young researchers who were either considering a path in biomedical science or had just returned from their PhD training. That kind of mentorship can have long-lasting effects across an entire system.

We have also built institutions that make international collaboration part of the structure, not something occasional. One example is CREATE, which brings leading overseas universities into close research partnership with our own institutions. When researchers share space, ideas and problems, new networks form and capabilities grow much faster.

More recently, we have also been organising parts of the system around large, multidisciplinary “Grand Challenges”. The first of these focuses on healthy and successful longevity. That reflects a broader shift in how many of the most important research questions now need to be tackled: not within isolated silos, but by bringing together multiple disciplines, institutions and international partners around a shared problem.

In the end, attracting strong people is not just about money. It is about whether talented researchers feel they can do meaningful work, collaborate with other excellent people and be part of an ecosystem that is serious, open and ambitious. And retention depends on much the same thing. Bright people want to be where they can keep growing, keep contributing and keep learning from others.