Yu Yin

Assistant Professor

Yu Yin

Yu Yin

Assistant Professor

Computer Vision, 3D Vision, Multimodal Learning, Embodied AI

Email: yu.yin@case.edu

Personal page: https://yin-yu.github.io/

Google Scholar: Profile

Location: Olin 606, CWRU

Team page: Back to Team

I am a tenure-track Assistant Professor in the Department of Computer & Data Science at Case Western Reserve University, where I lead the VU Lab. My research focuses on computer vision and 3D vision, multimodal large language models (MLLMs), and embodied AI systems, with the goal of building spatially grounded AI systems that can perceive, reason, and act in complex real-world environments.

At VU Lab, we study 3D vision and spatial representation, including Gaussian splatting (3DGS) and Nerual radiance fields (NeRF), with representative projects such as Reconstruction Matters, Segment then Splat, BARD-GS, and NeRFInvertor. We also investigate spatial intelligence for vision-language and embodied systems, including GSMem and our Spatial Intelligence in VLM survey. In addition, we develop multimodal methods and benchmarks for human-centered reasoning and decision-making, including VIVA, VIVA+, YesBut, YesBut-V2, and When Words Outperform Vision. Overall, our goal is to make multimodal and embodied AI systems more robust, trustworthy, and effective in real-world settings.

Education

  • Ph.D. in Computer Engineering, Northeastern University, Boston, USA (2019 - 2023)
  • M.S. in Electrical and Computer Engineering, Northeastern University, Boston, USA (2016 - 2018)
  • B.E. in Electrical and Information Engineering, Wuhan University of Technology, Wuhan, China (2012 - 2016)

Teaching

  • CSDS 570 - Deep Generative Models, Case Western Reserve University, USA, 2025-2026 Spring
  • CSDS 465 - Computer Vision, Case Western Reserve University, USA, 2024 Spring & Fall, 2025 Fall
  • CSDS 600 - Special Topics on Generative Models, Case Western Reserve University, USA, 2023 Fall
  • EECE 5642 - Data Visualization, Northeastern University, USA, 2021 Spring

Selected Awards

  • UCITE Glennan Fellowship, Case Western Reserve University, 2026
  • Breaking Boundaries Seed Grant, Case Western Reserve University, 2026
  • OpenAI Researcher Access Program, 2025
  • Teaching Award, Department of Computer and Data Sciences, Case Western Reserve University, USA, 2024
  • PhD Spotlight, Northeastern University, USA, 2023
  • Dissertation Fellowship, Northeastern University, USA, 2023
  • NSF I-Corps Grant, 2022
  • PhD Network Grant, Northeastern University, USA, 2019, 2023

Selected Academic Activities

  • Area Chair (AC)
    • ACL (2025-2026)
    • ICLR (2026)
    • NeurIPS (2026)
  • Workshop Organizer / Program Chair
    • ICCV - AMFG (2025)
    • ICCV - AMFG (2023)
    • CVPR - AMFG (2021)
    • FG - RFIW (2020)
  • Panel Reviewer
    • NSF/NIH, Smart Health (SCH) Program, 2026
  • Program Committee Member (2019-Now)
    • Journals: TPAMI, TIP, TNNLS, TCyber, TCSVT, IoT, Elsevier
    • Conferences: CVPR, ECCV, ICCV, NeurIPS, ICLR, ICML, ACL Rolling Review (ARR), AAAI, IJCAI, ACM MM

Selected Publications

  1. Segment then Splat: Unified 3D Open-Vocabulary Segmentation via Gaussian Splatting.
    Yiren Lu, Yunlai Zhou, Yiran Qiao, Chaoda Song, Tuo Liang, Jing Ma, Huan Wang and Yu Yin.
    In Advances in Neural Information Processing Systems (NeurIPS), 2025.
     
    @article{lu2025segment,
  title = {Segment then Splat: Unified 3D Open-Vocabulary Segmentation via Gaussian Splatting},
  author = {Lu, Yiren and Zhou, Yunlai and Qiao, Yiran and Song, Chaoda and Liang, Tuo and Ma, Jing and Wang, Huan and Yin, Yu},
  journal = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  status = {accepted},
  pdf = {https://arxiv.org/pdf/2503.22204v2},
  website = {https://yiren-lu.com/project_pages/Segment-then-Splat/},
  code = {https://github.com/luyr/Segment-then-Splat}
}

    

    

    2. 

  2. 
    
    BARD-GS: Blur-Aware Reconstruction of Dynamic Scenes via Gaussian Splatting.
    Yiren Lu, Yunlai Zhou, Disheng Liu, Tuo Liang and Yu Yin.
    In Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR), pp. 16532–16542, 2025.
    
    
    
    
    

    

    

    

    

    

    
    
    
        
    
    
        
    
    
    
    
        
    
    
        
    

    


    @inproceedings{lu2025bard,
  title = {BARD-GS: Blur-Aware Reconstruction of Dynamic Scenes via Gaussian Splatting},
  author = {Lu, Yiren and Zhou, Yunlai and Liu, Disheng and Liang, Tuo and Yin, Yu},
  booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)},
  pages = {16532--16542},
  year = {2025},
  status = {accepted},
  pdf = {https://arxiv.org/pdf/2503.15835},
  website = {https://yiren-lu.com/project_pages/BARD-GS/},
  code = {https://github.com/luyr/BARD-GS},
  data = {https://drive.google.com/drive/u/0/folders/1CRBQ_HR3yKhT3G9_ttTWA1PWXWL6DtsV}
}

    

    

    

    3. 

  3. 
    
    Praxis-vlm: Vision-grounded decision making via text-driven reinforcement learning. 
    Zhe Hu, Jing Li, Zhongzhu Pu, Hou Pong Chan and Yu Yin.
    In Advances in Neural Information Processing Systems (NeurIPS), 2025.
    
    
    
    
    

    

    

    

    

    

    
    
    
        
    
    
    
    
    
        
    
    

    


    @article{hu2025praxis,
  title = {Praxis-vlm: Vision-grounded decision making via text-driven reinforcement learning},
  author = {Hu, Zhe and Li, Jing and Pu, Zhongzhu and Chan, Hou Pong and Yin, Yu},
  journal = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  status = {accepted},
  pdf = {https://arxiv.org/pdf/2503.16965},
  code = {https://github.com/Derekkk/Praxis-VLM}
}

    

    

    

    4. 

  4. 
    
    Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions. 
    Zhe Hu, Tuo Liang, Jing Li, Yiren Lu, Yunlai Zhou, Yiran Qiao, Jing Ma and Yu Yin.
    In Advances in Neural Information Processing Systems (NeurIPS), vol. 37, pp. 47166–47188, 2024.
    (Oral)
    
    
    
    
    

    

    

    

    

    

    
    
    
        
    
    
        
    
    
    
    
        
    
    
        
    

    


    @article{hu2024cracking,
  title = {Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions},
  author = {Hu, Zhe and Liang, Tuo and Li, Jing and Lu, Yiren and Zhou, Yunlai and Qiao, Yiran and Ma, Jing and Yin, Yu},
  journal = {Advances in Neural Information Processing Systems (NeurIPS)},
  volume = {37},
  pages = {47166--47188},
  year = {2024},
  status = {accepted},
  note = {Oral},
  pdf = {https://openreview.net/pdf?id=bCMpdaQCNW},
  website = {https://vulab-ai.github.io/YESBUT_Homepage/},
  data = {https://huggingface.co/datasets/zhehuderek/YESBUT_Benchmark},
  code = {https://github.com/Derekkk/VIVA_EMNLP24}
}

    

    

    

    5. 

  5. 
    
    When ’YES’ Meets ’BUT’: Can AI Comprehend Contradictory Humor in Comics? 
    Tuo Liang, Zhe Hu, Jing Li, Hao Zhang, Yiren Lu, Yunlai Zhou, Yiran Qiao, Disheng Liu, Jierui Peng, Jing Ma and Yu Yin.
    In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2026.
    (Impact Factor: 20.4)
    
    
    
    
    

    

    

    

    

    

    
        
    
    
    
        
    
    
        
    
    
    
    
    
        
    

    


    @article{liang2026yesbut,
  title = {When 'YES' Meets 'BUT': Can AI Comprehend Contradictory Humor in Comics?},
  author = {Liang, Tuo and Hu, Zhe and Li, Jing and Zhang, Hao and Lu, Yiren and Zhou, Yunlai and Qiao, Yiran and Liu, Disheng and Peng, Jierui and Ma, Jing and Yin, Yu},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
  year = {2026},
  doi = {10.1109/TPAMI.2026.3688191},
  note = {Impact Factor: 20.4},
  status = {accepted},
  pdf = {https://arxiv.org/pdf/2503.23137.pdf},
  website = {/projects/yesbut-v2/},
  data = {https://huggingface.co/datasets/zhehuderek/YESBUT_Benchmark}
}