Personal profile

Research interests

Micheal Yang received the PhD degree (summa cum laude) from University of Bonn in 2011. From 06/2016 until 03/2024, he was Assistant Professor at University of Twente, heading a group working on scene understanding. Since 03/2024, he is Professor of Visual Computing at University of Bath.

His research is in the fields of Visual Computing and Computer Vision with specialization on Scene Understanding, Multimodal Learning, Deep Generative Models. He published over 150 papers in international journals and conference proceedings. He serves as Editorial Board Member of International Journal of Computer Vision, and recipient of the Best Science Paper Award at BMVC 2016 and The Willem Schermerhorn Award (2021). He co-organized 12 workshops with CVPR/ICCV/ECCV, and is guest editor of 4 journal special issues. He is regularly serving as program committee member of conferences and reviewer for international journals.

 

Prospective PhD students are welcome to contact him for general Computer Vision research projects, in particular on the topics of

  • 3D scene synthesis 
  • Scene graph generation
  • Multimodal learning

 

Our lab recruits one or two PhD students each fall. Prospective PhD students should apply to the Bath PhD Program in Computer Science.

 

Please visit his personal homepage for up to date information:

https://sites.google.com/site/michaelyingyang

 

Collaborators & Industrial Partners

Over the last years we have been collaborating with various scientific partners – such as Leibniz University Hannover, University of Twente, Zhejiang University, IIT Geova, Wuhan University, and more.

We have also been collaborating with various industrial research labs - such as Microsoft Research Asia, Amazon Research,  NEC Lab America, and Niantic.

Teaching interests

Main educational responsibilities are teaching topics on computer vision, deep learning, scene understanding, visual computing, AI.

Main Master thesis project topics: 

3D scene synthesis 

Visual question answering

Scene graph generation

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 11 - Sustainable Cities and Communities
  • SDG 15 - Life on Land

Education/Academic qualification

Habilitation (venia legendi), Leibniz Universität Hannover

May 2014Jun 2016

Award Date: 16 Jun 2016

Doctor of Engineering, Rheinische Friedrich-Wilhelms-Universität Bonn

Aug 2008Dec 2011

Award Date: 16 Dec 2011

Assistant Professor, University of Twente

Jun 2016Mar 2024

Postdoc, Technische Universität Dresden

Mar 2015May 2016

Postdoc, Leibniz Universität Hannover

May 2012Feb 2015

Keywords

  • QA75 Electronic computers. Computer science
  • Computer Vision
  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Scene Understanding

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Collaborations and top research areas from the last five years

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  • Robust Shape Fitting for 3D Scene Abstraction

    Kluger, F., Brachmann, E., Yang, M. Y. & Rosenhahn, B., 19 Mar 2024, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 46, 9, p. 6306-6325 20 p.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    File
    4 Citations (SciVal)
    242 Downloads (Pure)
  • Attribute-Centric Compositional Text-to-Image Generation

    Cong, Y., Min, M. R., Li, L. E., Rosenhahn, B. & Yang, M., Jul 2025, In: International Journal of Computer Vision. 133, 7, p. 4555-4570 16 p.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    3 Citations (SciVal)
  • DVLO4D: Deep Visual-Lidar Odometry with Sparse Spatial-temporal Fusion

    Liu, M., Yang, M., Liu, J., Zhang, Y., Li, J., Oude Elberink, S., Vosselman, G. & Cheng, H., 23 May 2025, 2025 IEEE International Conference on Robotics and Automation, ICRA 2025. Ott, C., Admoni, H., Behnke, S., Bogdan, S., Bolopion, A., Choi, Y., Ficuciello, F., Gans, N., Gosselin, C., Harada, K., Kayacan, E., Kim, H. J., Leutenegger, S., Liu, Z., Maiolino, P., Marques, L., Matsubara, T., Mavromatti, A., Minor, M., O'Kane, J., Park, H. W., Park, H.-W., Rekleitis, I., Renda, F., Ricci, E., Riek, L. D., Sabattini, L., Shen, S., Sun, Y., Wieber, P.-B., Yamane, K. & Yu, J. (eds.). U. S. A.: IEEE, p. 9740-9747 8 p. (Proceedings - IEEE International Conference on Robotics and Automation).

    Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

    Open Access
  • Guest Editorial: Special Issue on Multimodal Learning

    Yang, M. Y., Rota, P., Mancini, M., Morerio, P., Rosenhahn, B. & Murino, V., 31 May 2025, In: International Journal of Computer Vision. 133, p. 3079-3081 3 p.

    Research output: Contribution to journalEditorialpeer-review

  • Multimodal Rationales for Explainable Visual Question Answering

    Li, K., Vosselman, G. & Yang, M. Y., 10 Jun 2025, Proceedings - 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2025. U. S. A.: IEEE, p. 191-201 11 p. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops).

    Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

    Open Access
    1 Citation (SciVal)