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A student at NUS School of Computing and the NUS FinTech Lab, Sumit was one of just 14 university builders selected worldwide for the XRPL Student Builder Residency 2026 at Ripple’s London office. Sumit developed Verix, a blockchain-based task settlement system designed for AI agents, which he describes as “the trust layer for the agentic economy”.

Assistant Professor Ambuj Varshney and his WEISER research group are building a way around this. His project, “TinyLLM: A Framework for Training and Deploying Language Models at the Edge Computers”, has been selected for the 2026 Google Awards for Machine Learning Research and Education with TPUs.

NUS Presidential Young Professor Umang Mathur has been awarded the Temasek-Presidential Young Professorship (T-PYP) grant for his research on safer and more secure hardware design.

Training a large language model is not just about writing good code and pressing run. These models are spread across hundreds or thousands of processors – such as Google's Tensor Processing Units (TPUs), specialised accelerators designed to train and serve large-scale machine learning models – that must learn to work in lockstep: exchanging data, splitting tasks, staying synchronised. When something goes wrong, the whole system slows down, and expensive hardware sits idle. 

Singapore Vision Day 2026 returned to NUS School of Computing on 15 and 16 May, bringing together researchers, students, and industry practitioners for two days of talks, discussions, and research exchange across computer vision, graphics, embodied AI, multimodal AI, and robotics.

Artificial intelligence systems are growing larger, faster and more power-hungry by the month. But the question that increasingly preoccupies the computing world isn't what AI can do – it's whether the infrastructure beneath it can keep up.That challenge was at the heart of a lecture by Dr William Dally, Chief Scientist and Senior Vice President of Research at NVIDIA. at the NUS 120 Distinguished Speakers Series.