Filtered by: Paper Award
Home » Paper Award
15 April 2026
Two papers from the Augmented Human Lab have earned Honourable Mention Awards at ACM CHI 2026, the world’s leading conference in human-computer interaction. The award recognises the top 5% of accepted papers for their originality, rigour, and potential impact.
13 April 2026
A new model that teaches AI to understand and create music – across audio waveforms, symbolic notation, and text – has won Best Paper Award at the 32nd International Conference on Multimedia Modeling (MMM 2026), held in Prague, Czech Republic from 29 to 31 January 2026.
10 April 2026
Two faculty members from NUS Computing have been selected as StarTrack scholars by Microsoft Research Asia, Assistant Professor Yatao Bian and Sung Kah Kay Assistant Professor Jialin Li.
12 March 2026
Congratulations to alumnus Dr Deng Yimeng and collaborators on receiving multiple international Best Paper Awards for their research on digital inclusion.
26 December 2025
We’re proud to share that NUS Computer Science PhD student Zhou Zijian has won the Best Paper Award at the NeurIPS 2025 Workshop on Multi-Turn Interactions in Large Language Models
28 October 2025
NUS Computing PhD student Tianqi Song has been awarded Methods Recognitions at the ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2025) for her paper, “Multi-Agents are Social Groups: Investigating Social Influence of Multiple Agents in Human-Agent Interactions.”
17 October 2025
Professor Prateek Saxena from the National University of Singapore (NUS) School of Computing has been awarded the ACM CCS 2025 Test-of-Time Award for the paper “Demystifying Incentives in the Consensus Computer”, authored with Loi Luu, Jason Teutsch, and Raghav Kulkarni.
17 October 2025
Professor Reza Shokri from the NUS School of Computing and Google Research has been awarded the ACM CCS 2025 Test-of-Time Award for his work on “Privacy-Preserving Deep Learning,” co-authored with Professor Vitaly Shmatikov. This prestigious award recognises research that has had a profound and enduring influence on the field of privacy in AI.
