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Lun Wang

I am a senior research scientist at Google Deepmind, working on Gemini Live. My research interest focuses on multimodal LLMs, LLM safety, and privacy-preserving ML. I received my PhD degree in computer science from UC Berkeley, advised by Prof. Dawn Song in summer 2022. Before that, I received my Bachelor's degree with honors from Peking University in computer science in fall 2018.

Email / Google Scholar / Github / Twitter / LinkedIn

Selected Publication [full list]

Talks

  • 2024 Federated Learning on the Edge -- AAAI Spring Series Symposium 2024 @ Stanford: Reconcile Byzantine-robustness & Privacy in Federated Learning
  • 2021 Workshop on Federated Learning and Analytics @ Google: Federated frequency moments estimation and its application in feature selection
  • 2020 IC3 Blockchain Camp: "Aegis: Privacy-Preserving Data Analysis Framework
  • 2019 San Francisco Blockchain Week: Dynamic-Committee Proactive Secret Sharing
  • 2019 Large-Scale Consensus and Blockchains @ Simons Institute: CHURP: Dynamic-Committee Proactive Secret Sharing
  • Service

    • Journal Reviewer: Journal of Causal Inference, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Dependable and Secure Computing, Transactions on Machine Learning Research, Frontiers in Computer Science
    • Conference Reviewer: AAAI 2024, Interspeech 2024, ITCS 2023, RANDOM 2023, AISTATS 2022-2024, ICML 2021-2024, ICLR 2022-2024, Neurips 2021-2024, CCS 2021/2023, WWW 2021, ECML-PKDD 2021, PoPETS 2021-2024
    • Program Committee: FL-AsiaCCS’25, FedKDD 2024, TPDP 2024, CCS 2023, FL @ ICML 2023, SPAI 2020, WNA 2020