CV

Education

• Ph.D in Electrical and Computer Engineering, Univesity of Iowa, 2025 (expected)
• B.S. in Applied Physics, University of Science and Technology of China, 2019

Work experience

• University of Iowa

  Graduate Research Assistant | Aug. 2019 - May 2025 (Expected)

  • Develop a surgical navigation system that enables 3D visualization of spine anatomy and precise tracking of surgical tools, with the potential to enhance the accuracy and safety of spine procedures.
  • Develop a deep network model for cross-domain spine segmentation, trained on T2 MRI images and capable of accurately segmenting both T1 and T2 MRI images.
  • Develop an algorithm for fluorescence-to-color image registration using features detected by a convolutional neural network.

• Alcon Laboratories

  Research & Development Intern | June 2024 - Aug. 2024

  • Work on optimizing eye limbus and pupil detection programs with GPU acceleration. Employ CUDA to accelerate key stages of the eye image processing pipeline including rotation, filtering, edge detection, etc.

• Philips North America

  Research Scientist Intern | June 2023 - Aug. 2023

  • Develop deep network models for 3D cerebral angiography segmentation to enhance catheter navigation in endovascular procedures.

Skills

Publications

Multi-View Fusion-Based 3D Object Detection for Robot Indoor Scene Perception

Wang, L.; Li, R.; Sun, J.; Liu, X.; Zhao, L.; Seah, H.S.; Quah, C.K.; Tandianus, B. Multi-View Fusion-Based 3D Object Detection for Robot Indoor Scene Perception. Sensors 2019, 19, 4092. https://doi.org/10.3390/s19194092

Deep Convolutional Feature-Based Fluorescence-to-Color Image Registration

X. Liu, T. Quang, W. Deng and Y. Liu, "Deep Convolutional Feature-Based Fluorescence-to-Color Image Registration," 2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Lausanne, Switzerland, 2021, pp. 1-6, doi: 10.1109/MeMeA52024.2021.9478607.

Application of Hybrid Network of UNet and Feature Pyramid Network in Spine Segmentation

X. Liu, W. Deng and Y. Liu, "Application of Hybrid Network of UNet and Feature Pyramid Network in Spine Segmentation," 2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Lausanne, Switzerland, 2021, pp. 1-6, doi: 10.1109/MeMeA52024.2021.9478765.