AI, quantum computing and interdisciplinary research to reshape science: Heng Swee Keat
At the opening of the 14th Global Young Scientists Summit on Jan 6, National Research Foundation (NRF) chairman Heng Swee Keat laid out three forces that will redefine scientific work: AI, quantum computing, and deep interdisciplinary collaboration.
His message was clear: the tools are getting smarter, the hardware is catching up, and the problems worth solving demand teams that cross traditional boundaries.
AI: from tool to teammate
AI and machine learning now let researchers probe problems that were out of reach a few years ago. The upside is huge; the responsibility is bigger.
- Put AI to work on hard problems: hypothesis generation, literature triage, inverse design, and automated analysis pipelines.
- Build governance into your workflow: dataset provenance, audit trails, model cards, bias checks, and reproducibility standards aligned with widely adopted frameworks like the OECD AI Principles.
- Invest in talent that speaks both domains: scientists who code and engineers who understand experimental constraints.
Quantum computing: progress with purpose
Quantum processors operating near absolute zero can tackle classes of problems beyond classical systems. Useful applications are getting closer, even as fault tolerance remains a major engineering hurdle.
- Upskill your team on quantum algorithms, error mitigation, and benchmarking so you can evaluate real opportunities-not hype.
- Plan for access, not ownership: partner with platforms and labs for cryogenic setups and early hardware. Track standards work such as NIST's post-quantum cryptography to future-proof your systems.
- Target near-term wins: simulation of materials, catalysis, logistics optimization, and finance risk modeling where hybrid quantum-classical approaches help.
Interdisciplinary research: mandatory by design
Problems like climate change, healthy ageing, and secure supply chains don't fit inside a single discipline. The most valuable work happens at the seams.
- Organize around problems, not departments. Pair environmental science with engineering, data science, and policy from day one.
- Set shared data standards and common outcome metrics across teams. Publish protocols that others can reuse.
- Co-fund projects with industry and agencies to accelerate translation and adoption.
RIE2030: what it unlocks
Singapore's Research, Innovation and Enterprise (RIE) 2030 plan sets a strong signal for the next five years: $37 billion in total funding, about 1% of GDP. Within that, $3 billion will back two new programmes aimed at outcomes:
- RIE Grand Challenges: first focus on the ageing population.
- RIE Flagships: first project on semiconductors to establish Singapore as a strategic R&D node.
NRF will define target outcomes, map the bottlenecks, and fund coordinated portfolios to move the needle. Expect sustained investment in basic research talent, AI/data/advanced computing capabilities, and long-term upkeep of core infrastructure.
- More grants, fellowships, and investigatorships to develop local talent and attract top global researchers.
- Shared platforms and facilities to speed up high-quality, globally competitive work.
Keep an eye on NRF updates and calls for proposals: National Research Foundation (NRF).
What this means for your lab
- Codify AI use: set standards for data quality, validation, and model documentation; run red-team reviews for safety and misuse.
- Pilot quantum projects where problem structure fits; track error budgets and total cost per result, not just qubit counts.
- Pitch interdisciplinary proposals tied to ageing or semiconductor supply chains-priorities with clear translation paths.
- Align with industry partners early to secure testbeds, real datasets, and deployment routes.
Global Young Scientists Summit: scale and signal
This year's five-day summit runs through Jan 9 and hosts the largest cohort since its start in 2013: over 400 young researchers from 57 countries, with first-time participation from Kazakhstan, Mexico, and South Africa. Twenty-one eminent scientists-including Nobel laureates, Turing Award winners, and Millennium Technology Prize recipients-are also in attendance.
If you're strengthening your team's AI capability, these curated resources can help you move fast without wasting cycles: AI courses by job.
Your membership also unlocks:
