Researcher (Genius Nova)
Guangdong Lab of AI and Digital Economy (SZ)
[email protected]
https://scholar.google.com/citations?user=qb9STggAAAAJ&hl=en
About Me
Dr. Yao Shu (舒瑶) is currently a researcher at the Guangdong Lab of AI and Digital Economy (SZ) under the Genius Nova Programme, focusing on pioneering advancements in principled artificial intelligence research. Before that, Dr. Yao Shu was a senior researcher (Tencent Talent) at Tencent in 2023 and a Research Fellow at the National University of Singapore (NUS) in 2022. He received his PhD from the NUS School of Computing in 2022 under the esteemed guidance of Prof. Bryan Low, where he was awarded the IMDA Excellence in Computing Prize for the best PhD thesis in the school, as well as the Dean's Graduate Research Excellence Award for significant research achievements during his doctoral studies. Dr. Shu's research focuses on developing advanced algorithms that are both theoretically sound and practically useful through the synergistic interplay of optimization and learning. He has published about 20 papers in top AI conferences, including NeurIPS, ICLR, ICML, EMNLP, and UAI. He also serves as a reviewer for leading AI conferences such as NeurIPS, ICLR, ICML, AAAI, UAI, AISTATS, and AAMAS.
<aside>
Research Interests:
- Optimization and Decision-Making Algorithms
- Learning Dynamics and Theories
- Large Language Models
- Agentic AI
- Data-Centric AI
</aside>
Experience
Publication
Blog
News
- 2024.10: Our Ferret paper is accepted to FL@FM-NeurIPS’24 as an oral paper and our Flexora is accepted to FITML-NeurIPS’24!
- 2024.09: Our two papers on “Prompt Optimization” (ZOPO as spotlight!) and one paper on “Parallelized First-Order Optimization” are accepted to NeurIPS 2024!
- 2024.09: Our position paper on “Data-Centric AI in LLMs” is accepted to EMNLP 2024 Findings!
- 2024.09: Our Ferret paper is now available! Come and see how it significantly enhances the federated full-parameter tuning of Large Language Models!
- 2024.06: Our one paper on “Heterogeneous Federated Zeroth-Order Optimization” is accepted to Differentiable Almost Everything workshop @ ICML 2024 and two paper on “Prompt Optimization” are accepted to In-Context Learning workshop @ ICML 2024!
- 2024.05: Our paper on “Prompt Optimization” is accepted to ICML 2024!
- 2024.01: Our paper on “Training-free NAS” is accepted to ICLR 2024!
Awards
- Valedictorian for the class of Ph.D. graduates, School of Computing, NUS, 2023 (the script)
- IMDA Excellence in Computing Prize (Best Ph.D. Thesis), School of Computing, NUS, 2023 (the news)
- Dean’s Graduate Research Excellence Award, School of Computing, NUS, 2022 (the news)
- 2nd prize of 5th AutoML Challenge (AutoML for Temporal Relational Data) in the KDD Cup 2019 provided by 4Paradigm, ChaLearn and Microsoft, June 2019 (our solution, the news)
- Honor of Outstanding Student, 2015
- 2nd prize for The Chinese Mathematics Competitions (Non-professional), 2013
Services
Services