About Me

My name is Handong Zhao. I am a senior research scientist at Adobe Research, San Jose, CA. I obtained the Ph.D. degree at Department of Electrical & Computer Engineering, Northeastern University, Boston, MA. My current research interest includes (image) vision / (multilingual) language modeling at scale, text2image editing, and a few other high-level multimodal understanding tasks. I was the recipient of the National Science Foundation’s Innovation Corps (I-Corps™) program award as an entrepreneurial lead. Me at [Google Scholar] [DBLP] [Adobe Profile]

Recent News

  • [01/24] One ICLR-2024 accepted on self-supervised learning for entity segmentation.
  • [09/23] One NeurIPS-2023 paper accepted on InfoPrompt for NLU.
  • [07/23] One ICCV-2023 paper accepted on Spatial-Temporal Attention Controlled Diffusion Model.
  • [05/23] One ACL-2023 finding paper accepted on "Domain Adaptation for Named Entity Recognition".
  • [03/23] One CVPR-2023 paper accepted on "Uncovering Disentaglement Capability of Diffusion Models".
  • [01/23] Appointed as Associate Editor for for IEEE TCSVT.
  • [01/23] One ICLR-2023 paper accepted on "Continual Federated Learning".

  • More ...

    • [11/22] One AAAI-2023 paper accepted on "Compositional Image Retrieval".
    • [10/22] Two EMNLP-2022 papers accepted on "Multilingual Rep. Learning".
    • [08/22] Four CIKM-2022 papers accepted.
    • [06/22] One RecSys-2022 on "Conversational Bundle Rec" accepted as oral.
    • [06/22] Gave a talk on Federated Knowledge Composition in CVPR FedVision Workshop. [video recording]
    • [05/22] One KDD-2022 on "KG Infusion for Tabular Pre-training Models" accepted.
    • [04/22] One SIGIR-2022 on "Cross-domain Interaction Recommendation" accepted.
    • [03/22] One CVPR-2022 on "Fashion CLIP" and one L4DC-2022 on "Neural Spatiotemporal Point Process" accepted.
    • [02/22] Two ACL-2022 papers accepted on "Few-Shot Class-Incremental NER" and "Learning Adaptive Axis Attentions in Fine-tuning (Finding paper)".
    • [01/22] One paper "Neural Contextual Bandits with Deep Representation and Shallow Exploration" accepted by ICLR-2022.
    • [01/22] One paper on "Federated Learning for Multilingual NLU" accepted by WWW-2022.
    • [12/21] One paper on "Continual Federated Learning" accepted by ICLR-2023.
    • [12/21] One paper on "Cross-Domain Clustering" accepted by AAAI-2022 student abstract and poster program.
    • [10/21] Two papers on "Continual NER" and "User-in-the-loop NER" accepted by NeurIPS ENLSP Workshop.
    • [09/21] Two papers on "KD-based Graph Similarity Computation " and "Document Representation Learning" accepted by NeurIPS-2021.
    • [08/21] One short paper on "Sequential Recommender System" accepted by CIKM-2021.
    • [07/21] Two papers on "Source-Free DA" and "Semi-Supervised DA" accepted by ICCV-2021.
    • [05/21] One paper on "Explainable Column Annotation" accepted by KDD-2021.
    • [05/21] One paper on "KG-based Commonsense Reasoning" accepted by Findings of ACL-2021.
    • [04/21] I'm co-organizing The 3rd Workshop on Continual and Multimodal Learning for Internet of Things (CML-IOT), at IJCAI-2021. The qualified papers are planned to invited as submissions to a journal special issue.
    • [03/21] One CVPR-2021 on "Document Representation Learning" and one NAACL-2021 on "KG Enrichment" got accepted.
    • [01/21] One ICLR-2021 on "Learning to Deceive KG" accepted.
    • [12/20] One NeurIPS-KR2ML workshop paper on "KG-based Commonsense Reasoning" accepted.
    • [11/20] One paper on "Learnable Subspace Clustering" accepted by TNNLS. [arXiv].
    • [09/20] One NeurIPS-2020 on "Self-Supervised Relationship Probing" accepted.
    • [07/20] One ECCV-2020 on "Open Domain Image Manipulation" and one CIKM-2020 on "KG Reasoning for Recommendation" accepted.
    • [06/20] One paper on "Linear Quadratic Regulator" accepted by ICML-2020.
    • [05/20] One paper on "Personalized Image Retrieval" accepted by KDD-2020.
    • [04/20] One survey paper on "Representation Learning for User Modeling" was accepted by IJCAI-2020.
    • [03/20] Our IJCAI-2020 tutorial "Robust Multi-view Visual Learning: A Knowledge Flow Perspective" was accepted (with prof. Zhengming Ding and prof. Ming Shao).
    • [02/20] One paper on "Cross-domain Document Object Detection" was accepted by CVPR-2020.
    • [11/19] One SoCC-2019 poster and one BigData-2019 paper accepted.
    • [09/19] I gave a talk on "Multi-modal Representation Learning", invited by Prof. Hongfu Liu at Brandeis.
    • [07/19] One ICCV-2019 paper got accepted. Congratulations to Jiuxiang.
    • [04/19] Two KDD-2019 papers accepted on the topics of "Sequential Adversarial Learning" and "Interpretable User Modeling".
    • [02/19] My FIRST summer intern Jiuxiang's work on "Scene Graph Generation" got accepted by CVPR-2019.
    • [02/19] Co-host (with Myra and Subrata) session "AI For System" won Top Ten Session in Adobe-TechSummit-2019. Got my first trophy at Adobe.
    • [12/18] Accepted the invitation to serve as PC member for IJCAI-2019.
    • [11/18] Will host a mini-summit, "Analyze, Predict, and Visualize: when RNNs meet Adobe", at Adobe-TechSummit-2019 with Sungchul Kim.
    • [10/18] I have one paper accepted by WSDM-2019 (Acceptance Rate: 16.4%).
    • [10/18] AAAI-2019 Tutorial "Deep Multi-view Data Analytics" was accepted (with Allan Ding and Hongfu Liu).
    • [05/18] Accepted the invitations to serve as PC for NIPS-2018 and SPC for AAAI-2019.
    • [03/18] One book proposal (with Allan and Prof. Raymond Fu) is accepted by Springer.
    • [03/18] I accepted the invitation to serve as a member of the Program Committee for CVPR-2018 workshop on Analysis and Modeling of Faces and Gestures (AMFG).
    • [02/18] I accepted the invitation to serve as a member of the Program Committee for ICMLA-2018.
    • [01/18] I have one paper accepted by WACV-2018.

    • Talk/Tutorial

    1. Keynote: Federated Knowledge Composition
      FedVision: International Workshop on Federated Learning for Computer Vision
      In conjunction with CVPR 2022, New Orleans, Louisiana. [Recording]
    2. Tutorial: Robust Multi-view Visual Learning: A Knowledge Flow Perspective
      Jointly organized with Zhengming Ding and Ming Shao
      IJCAI-2020, virtual.
    3. Tutorial: Analyze, Predict and Visualize: When RNNs Meet Adobe
      Jointly organized with Sungchul Kim, Fan Du and Sana Malik
      Adobe Tech Summit 2019, San Francisco, CA, February 2019.
    4. Tutorial: Deep Multi-View Visual Data Analytics
      Jointly organized with Zhengming Ding and Hongfu Liu
      AAAI-2019, Honolulu, Hawaii, January 2019.
    5. Tutorial: Multi-view Face Representation
      Jointly organized with Zhengming Ding and Yun Raymond Fu
      FG-2017, Washington, D.C., May 2017.