I am Yimu Wang, a second-year Ph.D. student at UWaterloo. I obtained my master’s degree under the supervision of Prof. Lijun Zhang in the LAMDA Group led by Prof. Zhihua Zhou at Nanjing University. I was honored to spend a wonderful RA time at Tsinghua University with Prof. Jingjing Liu and Prof. Yang Liu and amazing experiences at Tencent Lightspeed & Quantum Studios, Alibaba, Netease Games, and Megvii. I also had a wonderful journey at Derivatives-China as a quant research intern.

  • Multi-modal Learning
  • Point Cloud Understanding
  • PhD in Computer Science, 2022 - Now

    University of Waterloo

  • MSc in Computer Science and Technology, 2018 - 2021

    Nanjing University

  • BSc in Software Engineering, 2014 - 2018

    Northwestern Polytechnic University

Recent News

All news»

  • [2023-10-07] 🎉🎉 Three papers got accepted by EMNLP 2023 (one main paper and two findings)! Congratulations to all the coauthors!
  • [2023-09] 🎉🎉 One paper got accepted by NeurIPS 2023! Congratulations to all the coauthors!
  • [2023-04] I have been awarded by the CVPR's DEI fund for traveling to Vancouver!
  • [2023-02] 🎉🎉 One paper got accepted by CVPR 2023! Congratulations to all the coauthors!
  • [2023-01] 🎉🎉 One paper got accepted by ICLR 2023! Congratulations to all the coauthors!
  • Selected Publications and Preprints

    (2023). Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards. NeurIPS.


    (2023). InvGC: Robust Cross-Modal Retrieval by Inverse Graph Convolution. Findings of EMNLP.


    (2023). Video-Text Retrieval by Supervised Sparse Multi-Grained Learning. Findings of EMNLP.


    (2023). Cooperation or Competition: Avoiding Player Domination for Multi-target Robustness by Adaptive Budgets. IEEE/CVF Conference on Computer Vision and Pattern Recognition.

    PDF Cite Arxiv Supp

    (2023). Multimodal Federated Learning via Contrastive Representation Ensemble. International Conference on Learning Representations.

    PDF Cite Arxiv

    (2022). Multi-View Fusion Transformer for Sensor-Based Human Activity Recognition. arXiv:2202.12949.

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    (2021). Deep Unified Cross-Modality Hashing by Pairwise Data Alignment. International Joint Conference on Artificial Intelligence.

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    (2021). Classification of neurofibromatosis-related dystrophic or nondystrophic scoliosis based on image features using Bilateral CNN. Med Phys.

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    (2020). Piecewise Hashing: A Deep Hashing Method for Large-Scale Fine-Grained Search. Pattern Recognition and Computer Vision.

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    (2020). Searching Privately by Imperceptible Lying: A Novel Private Hashing Method with Differential Privacy. ACM International Conference on Multimedia.

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    (2020). Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs. International Joint Conference on Artificial Intelligence.

    PDF Cite Arxiv

    (2020). An Adversarial Domain Adaptation Network For Cross-Domain Fine-Grained Recognition. IEEE Winter Conference on Applications of Computer Vision (WACV).

    PDF Cite Project


    Research Assitant
    October 2021 – April 2022 Beijing, China
    Researching on multi-modal learning (Retrieval) and Federated Learning under the supervision of Jingjing Liu and Yang Liu. We propose a framework that is able to distill knowledge from private users’ unimodal data and then fuse that knowledge into the multi-modal server model. This project has been accepted by ICLR 23.
    Research Intern
    May 2021 – September 2021 Hangzhou, China
    Researching on multi-modal anomaly detection. We collected multi-modal user data to analyze the pattern of anomaly face recognition and designed a novel architecture that is able to detect most of the anomaly data.
    Quan Research Intern
    January 2021 – April 2021 California
    Developing and researching powerful prediction systems for A-Shares.
    Research Intern
    August 2020 – September 2020 Hangzhou, China
    Researching on the project of 3D face reconstruction from a single RBG image.
    Research Intern
    June 2020 – July 2020 Shenzhen, China
    Participate in Abnormal Text and Image Detection. We designed a novel framework for detecting text and image that is not allowed in the game.
    Research Intern
    January 2018 – November 2019 Beijing (Nanjing), China
    Participate in several research projects (GAN, Domain Adaptation, Fine-grained Image Analysis and Hashing) at Nanjing Research. Most of the projects have been written and published at conferences, e.g., WACV.