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Xuelian Cheng

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Xuelian Cheng

Dr

 https://orcid.org/0009-0002-7014-5304

Accepting PhD Students

PhD projects

The candidate will be working on geometric vision and robotics-related topics. Research directions include Computer Vision, medical image computing, 3D scene understanding, and reconstruction techniques for clinical decision support and diagnosis, as well as robotic surgery intelligence. Our group has previously published work in top academic conferences and journals such as CVPR, EMNLP, AAAI, KDD, NeurIPS, ICLR, ICCV, TPAMI, and MICCAI etc.. Feel free to reach out if this opportunity piques your interest!

20172026

Research activity per year

Personal profile

Biography

Dr. Xuelian Cheng is currently a Research Fellow at Monash Suzhou and an Adjunct Lecturer at Monash University, Australia. Her research covers visual geometry and low-level vision, including depth estimation, stereo matching, 3D reconstruction, and embodied AI for navigation and manipulation. Among these, image-guided surgery is her flagship research area, supported by the Natural Science Foundation of Jiangsu Province (Grant No. BK20250441) and the Suzhou Industrial Park University Cooperation and Development Bureau. She also contributed to diverse research projects with industrial companies including Tencent (Canberra XR Lab), IIAI, Airdoc, and SenseTime. The outcomes led to publications at top ML/CV and medical imaging conferences.

 

Research Interests

Previous representative works include deep learning for 3D visual perception and reconstruction, automated machine learning (AutoML), and video analysis and object detection. With a keen interest in the interdisciplinary realm of machine learning, computer vision, medical image analysis, and robotic surgery intelligence, she aspires to leverage her expertise in ML/CV to pioneer novel approaches for disease detection, diagnosis, and monitoring, as well as surgical interventions. Her focus extends to applying AR/VR/XR technologies to medical imaging data for educational purposes, aiming to make significant strides in enhancing patient outcomes and revolutionizing medical practice.

Accepting prospective PhD students. If you're interested in working with her, please send an email including your CV and transcripts.

 

Teaching Experience

Lecturer

FIT5047 Fundamentals of artificial intelligence, S1, Monash University (Suzhou), 2025↝

FIT5226 Multi agent systems and collective behaviour, S1, Monash University (Suzhou), 2025↝

FIT5216 Modelling discrete optimization problems, S1, Monash University (Suzhou), 2024↝2025

FIT5037 Network security, T3, Monash University (Suzhou), 2024↝2025

FIT5222 Planning and automated reasoning, T3, Monash University (Suzhou), 2024↝

Teaching Assistant

ECE4179 Neural networks and deep learning, Monash University (Clayton), 2020↝2022

ECE4076 Computer vision, Monash University (Clayton), 2020↝2022

 

Research area keywords

  • Computer Vision
  • Medical Imaging
  • Machine Learning

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):

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 5 - Gender Equality
    SDG 5 Gender Equality
  3. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
Explore network further

  • OphNet: A Large-Scale Video Benchmark for Ophthalmic Surgical Workflow Understanding

    Hu, M., Xia, P., Wang, L., Yan, S., Tang, F., Xu, Z., Luo, Y., Song, K., Leitner, J., Cheng, X., Cheng, J., Liu, C., Zhou, K. & Ge, Z., 2025, Computer Vision – ECCV 2024 - 18th European Conference Milan, Italy, September 29–October 4, 2024 Proceedings, Part IV. Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T. & Varol, G. (eds.). Cham Switzerland : Springer, p. 481-500 20 p. (Lecture Notes in Computer Science; vol. 15062).

    Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

    20   Link opens in a new tab Citations (Scopus)

  • Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding

    Tang, F., Liu, C., Xu, Z., Hu, M., Huang, Z., Xue, H., Chen, Z., Peng, Z., Yang, Z., Zhou, S., Li, W., Li, Y., Song, W., Su, S., Feng, W., Su, J., Lin, M., Peng, Y., Cheng, X. & Razzak, I. & 1 others, Ge, Z., 2025, Proceedings, 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2025. Mortensen, E. (ed.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 26147-26159 13 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

    Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

    19   Link opens in a new tab Citations (Scopus)

  • Autonomous novel class discovery for vision-based recognition in non-interactive environments

    Zhang, X., Liu, F., Cheng, X., Yan, S., Liao, Z. & Ge, Z., 2024, In: Cognitive Robotics. 4, p. 191-203 13 p.

    Research output: Contribution to journal › Article › Research › peer-review

    Open Access

  • Declaration of Computational Neurosurgery

    Di Ieva, A., Suero Molina, E., Somerville, M. A., Beheshti, A., Staartjes, V. E., Serra, C., Theodore, N., Elliott, J. M., Wesselink, E. O., Russo, C., Pilitsis, J. G., Bennett, C. C., Wu, S., Hammond, F. M., Lozano, A. M., Cusimano, M. D., Davidson, J. M., Castellano, J. F., Okonkwo, D. O. & Arefan, D. & 43 others, Lee, C. C., Zanier, O., Da Mutten, R., Matula, C., Rutka, J. T., Pease, M., Liu, S., Stummer, W., Matulionyte, R., Yang, H., Yuwen, C., Cheng, X., Fan, H., Wang, X., Ge, Z., Cepeda, S., Sheehan, J. P., Yang, J. Y. M., Hamer, R. P., Cohen-Gadol, A., Hansford, J. R., Savage, G., Sowman, P. F., Stewart, C., Kateb, B., Sherif, C., Perperidis, A., Guller, A., Hanft, S., D’Amico, R. S., Sav, A., Cong, C., Song, Y., Nicolosi, F., Wiedmann, M. K. H., Barone, D. G., Noorani, I., Magnussen, J., Krieg, S. M., Meling, T. R., De Ridder, D., Lawton, M. T. & Rosenfeld, J. V., 2024, Computational Neurosurgery. De Ieva, A., Molina, E. S., Liu, S. & Russo, C. (eds.). 1st ed. Cham Switzerland: Springer, p. 11-20 10 p. (Advances in Experimental Medicine and Biology; vol. 1462).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter (Book) › Research › peer-review

    1   Link opens in a new tab Citation (Scopus)

  • Deep Learning: A Primer for Neurosurgeons

    Yang, H., Yuwen, C., Cheng, X., Fan, H., Wang, X. & Ge, Z., 2024, Computational Neurosurgery. Di Ieva, A., Suero Molina, E., Liu, S. & Russo, C. (eds.). 1st ed. Cham Switzerland: Springer, p. 39-70 32 p. (Advances in Experimental Medicine and Biology; vol. 1462).

    Research output: Chapter in Book/Report/Conference proceeding › Chapter (Book) › Research › peer-review

    2   Link opens in a new tab Citations (Scopus)
View all 15 research outputs