Wanru Zhao

I'm a PhD student in Computer Science at University of Cambridge, advised by Prof. Nic Lane at the Cambridge Machine Learning Systems Lab (CaMLSys). I'm also a member of Cambridge AI Safety Lab, working on AI Alignment and Interpretability. Prior to that, I obtained my MPhil in Advanced Computer Science at Cambridge as well.

I’m currently visiting the Vector Institute, working with Colin Raffel at the University of Toronto. I was a research intern at Microsoft Research, mentored by Alessandro Sordoni and Lucas Caccia.

My research focuses on:

• Modular, distributed/decentralised training (model merging, Mixture-of-Experts) and decentralised inference;
• Data attribution/selection/curation/balancing/mixing, synthetic data generation and curriculum design for foundation model training;
• Compositional reasoning of large language models (in math and coding domains) and multi-agent systems

Email  /  Google Scholar  /  GitHub  /  Twitter  /  Bluesky

• [Sept 2025] One conference paper and one workshop paper accepted to NeurIPS 2025! See you in San Diego 🇺🇸 / Mexico City 🇲🇽
• [Jun 2025] Two workshop papers accepted to ICML 2024 AI for Math Workshop!
• [Jan 2025] Our workshop proposal on Modular, Collaborative and Decentralized Deep Learning accepted to ICLR 2025! See you in Singapore 🇸🇬
• [Feb 2025] One paper accepted to AAMAS 2025!
• [Feb 2025] One paper accepted to MLSys 2025!
• [Jan 2025] One paper accepted to ASP-DAC 2025!
• [Sept 2024] Two conference papers and one workshop paper accepted to NeurIPS 2024! See you in Vancouver 🇨🇦
• [Feb 2024] One conference paper and two workshop papers accepted to ICLR 2024! See you in Vienna 🇦🇹
• [Mar 2023] Our team got the winner of the US-UK Privacy-Enhancing Technologies Prize Challenges! We will present our solution at Innovation and Technology's Centre for Data Ethics and Innovation (CDEI) in London at the end of May. Check out the report on the Cambridge University website!
• [Mar 2023] One paper accepted to FAccT 2023!

(This list is not comprehensive and is being updated. For a complete list of publications, please visit my Google Scholar profile.)

• Microsoft Research, with Alessandro Sordoni on modular and synthetic data generation for reasoning tasks and coding agents, 2025
• Vector Institute, with Colin Raffel and Nicolas Papernot on training data curation and multi-agent mechanistic design, 2024
• Amazon AI Lab, with Minjie Wang and Zheng Zhang on Deep Graph Library and its interpretability toolkits GNNLens2 , 2021
• SenseTime Research, with Ruihao Gong and Fengwei Yu on model quantization and compression, 2019