NTU

NTU's core AI units:

• College of Computing and Data Science (CCDS): upgraded from SCSE in 2024, integrating computer science and data science
• S-Lab: joint laboratory with SenseTime, focused on vision and generative models
• **Centre for Frontier AI Research (with A*STAR)**: joint research centre
• NTU Institute for AI Research: cross-disciplinary AI research platform
• NTU Garage @ DBS / SIA: joint AI application labs with enterprises

Signature research directions:

• Continual Learning: NTU is a global hub for this area
• Computer Vision: the S-Lab–SenseTime collaboration produces a steady stream of top-tier conference papers
• Robotics + AI: NTU's engineering background gives it an edge in robotic AI
• AI for Engineering: in materials, chip design, and intelligent manufacturing

Internationally, NTU has deep collaborations with SenseTime, Alibaba DAMO Academy, and Microsoft Research Asia — making it the primary interface for China's AI scene in Singapore.

NTU has a clean differentiation from NUS in AI:

• NUS: leans towards foundational research, societal impact, and policy research
• NTU: leans towards engineering applications, industry partnerships, and vision/robotics

NTU's paper output even surpasses NUS in some sub-areas (CV, Continual Learning, Robotics). The S-Lab–SenseTime collaboration gives NTU consistent presence at top venues like CVPR / ICCV / ECCV.

But NTU also faces a problem: deep entanglement with China's AI scene brings geopolitical risk. After S-Lab's partner SenseTime was sanctioned by the US, NTU has had to rebalance its international collaboration portfolio. This is also why NTU has been strengthening ties with Google DeepMind and AWS in recent years.

Technically, NTU's presence in GenAI is weaker than NUS — it has no SEA-LION-class flagship project, and outputs are mostly single-point breakthrough papers. This is exactly what the 2024 CCDS upgrade is trying to address: consolidating fragmented AI research forces into more systematic output.

In Singapore's AI strategy, NTU plays the role of "engineering execution + international collaboration" pivot.

Across the seven transmission levers:

• Lever 1 (Foundational Research): complementary to NUS, NTU leans towards vision, robotics, and engineering AI
• Lever 2 (Talent): NTU CCDS is the other major pipeline for Singapore's AI engineers
• Lever 3 (Industry Application): NTU Garage's joint labs with DBS, SIA, and other large enterprises are a model for industrial AI deployment

Take: NTU's "industry partnership" model is the commercialisation template for Singapore's applied AI research — more grounded than NUS, more flexible than A*STAR. The "university + large enterprise joint lab" pattern is one of the most effective mechanisms for industrial AI deployment in Singapore.

But NTU's involvement in national-level AI flagship projects lags NUS — AISG is not on the NTU campus, and SEA-LION is led primarily by NUS teams. A key question for the NAIS 2.0 era: how does NTU find a differentiated position in the national narrative (for example, becoming the national centre for "robotic AI" or "vision AI")?

Variables to watch: whether the post-integration CCDS produces flagship projects, the future of the SenseTime collaboration, and whether NTU can catch up in GenAI.