CV

For the PDF version, please refer to file cv_haoyulu

Education

• B.S. in Computer Science and Technology, School of Artificial Intelligence, Beijing Normal University, 06/2024
  • GPA: 3.8/4.0, Rank: 5/53
  • Thesis title: High-quality 3D Image Reconstruction from Low-dose PET Image Based on Diffusion Model
  • Relevant Courses (selected):
    • Compulsory: Data Structure (95), Principles of Computer Composition (95), Algorithm Design and Analysis (94), Probability Theory and Stochastic Process (93)
    • Optional: Introduction to Machine Learning (97), Multimedia Technology (93), Introduction to Big Data (95), Programming in JAVA (95)
• Ph.D. Student in Biomedical Engineering, Faculty of Engineering and IT, University of Melbourne
  • Advisors: Prof. Leigh Johnston, Dr. Catherine Davey
  • Prosposed thesis title: Physics Informed AI-based PET Image Reconstruction

Work Experience

• Sept. 2022 - Jun. 2024: Research Assistant
  • Key Laboratory of Beam Technology of Ministry of Education, Beijing Normal University
  • Duties included:
    • Explored the combination of computer science and medical imaging techniques, especially in fields of positron emission tomography (PET) and Compton imaging
    • Implemented models for medical image classification and segmentation from U-net to recent Segment Anything Model (SAM), having gained insights into both the imaging principle and related downstream tasks
    • Worked on physics-based imaging correction using methods of deep learning and reinforcement learning-aided imaging
  • Supervisor: Prof. Jianyong Jiang
• Apr. 2023 - Oct. 2023: Research Assistant
  • Natural Hazards Remote Sensing Lab, Peking University
  • Duties included:
    • Implemented the domain adaptation segmentation model for Multi-Annual Inventorying of Retrogressive Thaw Slumps Using Domain Adaptation, having achieved an F1 score of 0.829 and a recall rate of 0.934, outperforming CycleGAN and fine-tuning
    • Adapted Segment Anything Model (SAM) to correctly segment craters on planet surface
  • Supervisor: Prof. Xie Hu
    • Co-advised by Prof. Shanghang Zhang

Publications

A virtual-pinhole PET device for improving contrast recovery and enhancing lesion detectability of a one-meter-long PET scanner: a simulation study.

Jiang, J., Hua, J., Wang, H., Yuan, Z., Meng, Y., Lu, H., ... & Tai, Y. C. (2023). "A virtual-pinhole PET device for improving contrast recovery and enhancing lesion detectability of a one-meter-long PET scanner: a simulation study." Physics in Medicine and Biology.. 68(14).

QUANTOF: multi-GPU-based list-mode fully quantitative TOF PET image reconstruction.

Yuan, Z., Zhan, F., Lu, H., Li, C., Hou, Y., Wang, H., ... & Jiang, J. (2024, October). QUANTOF: multi-GPU-based list-mode fully quantitative TOF PET image reconstruction. In 2024 IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD) (pp. 1-1). IEEE.

Multi-Annual Inventorying of Retrogressive Thaw Slumps Using Domain Adaptation

Lin, Y., Hu, X., Lu, H., Niu, F., Liu, G., Huang, L., et al. (2025). Multi-annual inventorying of retrogressive thaw slumps using domain adaptation. Journal of Geophysical Research: Machine Learning and Computation, 2, e2024JH000370. https://doi.org/10.1029/2024JH000370

Honors and Awards

Selected by significance and recency

• Melbourne Research Scholarship, University of Melbourne, Mar. 2024
• Silver Medal, Internationally Genetically Engineered Machine Competition (Modelling), Nov. 2022
• 1st Prize Scholarship (10%), Beijing Normal University, Oct. 2022 & Oct. 2021
• 1st Prize, National English Contest for College Students, Oct. 2022
• Excellent Student Cadre, Beijing Normal University, Oct. 2022
• 2nd Prize, Beijing College Students’ `Internet+’ Innovation and Entrepreneurship Competition, Aug. 2022
• Honorable Mention, Interdisciplinary Contest In Modelling, May. 2022
• Merit Student, Beijing Normal University, Oct. 2021

Skills and Interest

Programming: proficient in

• Programming languages: C/C++, Python, MATLAB, C#, Java
• Deep learning frameworks: PyTorch, TensorFlow
• Development environment configuration across multiple OS platforms, including Linux

Languages:

• English - Fluent
  • TOEFL: 108
    • Reading: 29/30
    • Listening: 26/30
    • Speaking: 26/30
    • Writing: 27/30
  • GRE: 327+3.5
    • Verbal reasoning: 158/170
    • Quantitative reasoning: 169/170
    • Writing: 3.5/6.0
  • CET-6: 605

Miscellaneous

• Swimming
• Climbing
• Photography
• Hiking
• Basketball