Unveiling the Tapestry: the Interplay of Generalization and Forgetting in Continual Learning
Z Shi, J Jing, Y Sun, JH Lim, M Zhang
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2025
Jie Jing
PhD Candidate in Computer Vision
Summary
PhD candidate specializing in computer vision and deep learning for medical imaging applications. Demonstrated expertise in developing novel denoising algorithms, contrastive learning frameworks, and continual learning systems. Published papers with strong focus on practical applications in medical image processing and computational vision.
Research Experience
Visiting PhD Student
September 2023 - April 2025A*STAR & Nanyang Technological University · Singapore
- Conducted advanced research in contrastive learning and continual learning dynamics.
- Developed novel algorithms for image memorability analysis in computer vision tasks.
- Authored multiple peer-reviewed publications on generalization and forgetting mechanisms.
- Collaborated with international research teams on cutting-edge deep learning projects.
Graduate Research Assistant
2020 - PresentSichuan University · Chengdu, China
- Pioneered unsupervised medical image denoising techniques using contrastive learning.
- Developed motion correction algorithms for MRI imaging using compressed sensing.
- Led research on low-dose CT denoising without high-quality reference data.
- Achieved oral presentation recognition at MICCAI 2023 (top 12% of submissions).
Publications
Unforgettable Lessons from Forgettable Images: Intra-Class Memorability Matters in Computer Vision Tasks
J Jing, Q Lin, S Han, L Schiatti, YL Kuo, M Zhang
arXiv preprint arXiv:2412.20761, 2024
Generalizable MRI Motion Correction via Compressed Sensing Equivariant Imaging Prior
Z Wang, M Ran, Z Yang, H Yu, J Jing, T Wang, J Lu, Y Zhang
IEEE Transactions on Circuits and Systems for Video Technology, 2024
Inter-slice Consistency for Unpaired Low-dose CT Denoising Using Boosted Contrastive Learning
J Jing, T Wang, H Yu, Z Lu, Y Zhang
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2023
Oral Presentation (Top 12% of submissions)
Training Low Dose CT Denoising Network Without High Quality Reference Data
J Jing, W Xia, M Hou, H Chen, Y Liu, J Zhou, Y Zhang
Physics in Medicine & Biology, 2022
Education
PhD, Software Engineering
Sichuan University
2022 - Expected 2026
Master, Software Engineering
Sichuan University
2020 - 2022
Bachelor, Software Engineering
Sichuan University
2016 - 2020
Technical Skills
Programming & Frameworks
PythonPyTorchTensorFlowMATLABC++CUDA
Computer Vision & AI
Deep Learning ArchitectureContrastive LearningContinual LearningMedical Image ProcessingNeural Network Optimization
Research Methodologies
Large-scale Data AnalysisAlgorithm DevelopmentStatistical AnalysisScientific Writing
Medical Imaging
CT/MRI ProcessingImage DenoisingMotion CorrectionLow-dose Imaging
Professional Skills
Research Leadership
Led multiple collaborative research projects with international teams.
Technical Communication
Presented research findings at top-tier conferences and workshops.
Mentoring
Guided junior researchers and students in deep learning methodologies.
Cross-functional Collaboration
Worked effectively with medical professionals and engineers.