Jiancheng (JC) Yang is a researcher at Swiss Federal Institute of Technology Lausanne (EPFL), where he collaborates with Prof. Pascal Fua on AI for health and 3D vision. He earned the Bachelor's and PhD degrees at Shanghai Jiao Tong University, and was a visiting research fellow in the VCG at Harvard University and the CVLab at EPFL. Moreover, JC co-founded and served as CTO of a medical AI startup in Shanghai, which successfully raised millions of dollars in funding.
JC has authored 50+ papers in leading journals and conferences, including Cancer Research, eBioMedicine, TMI, MedIA, CVPR, MICCAI and NeurIPS. He serves as an Area Chair for MICCAI 2024 and MIDL 2025, and regularly reviews for top-tier venues. He has also organized several MICCAI challenges and tutorials. His contributions have been recognized, including being listed among the Top 2% Scientists Worldwide and Forbes 30 Under 30.
As a personal interest, JC is the initiator and organizer of the HIT Webinar (hit-webinar.com), a Chinese-language webinar series focusing on healthcare, artificial intelligence, and cutting-edge technology. This fully open, non-profit initiative has hosted 80+ sessions since its launch in April 2022.
- M3DV/RibFrac-Challenge: MICCAI 2020 RibFrac Challenge: Rib Fracture Detection and Classification (3D Instance Segmentation)
- M3DV/LeFusion: LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion Models
- MedMNIST/MedMNIST: [pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
- M3DV/ACSConv: [IEEE JBHI] Reinventing 2D Convolutions for 3D Images - 1 line of code to convert pretrained 2D models to 3D!
- M3DV/AlignShift: [MICCAI'21 & MICCAI'20] A Codebase for Universal Lesion Detection (DeepLesion SOTA)
- M3DV/pulmonary-tree-repairing: [MICCAI'23] Topology Repairing of Disconnected Pulmonary Airways and Vessels: Baselines and a Dataset
- M3DV/pulmonary-tree-labeling: [MedIA‘25] Efficient anatomical labeling of pulmonary tree structures via deep point-graph representation-based implicit fields
- M3DV/NeAR: [MICCAI'22] Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis
- M3DV/ImPulSe: [MICCAI'22] What Makes for Automatic Reconstruction of Pulmonary Segments
- M3DV/RibSeg: [MICCAI'21 & TMI'23] RibSeg Dataset and Point Cloud Baselines for Rib Segmentation from CT Scans
- M3DV/FracNet: [eBioMedicine] Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet
- M3DV/SimTA: [MICCAI'20] MIA-Prognosis: A Deep Learning Framework to Predict Therapy Response
- TrustworthyDL/LeBA: [NeurIPS'20] Learning Black-Box Attackers with Transferable Priors and Query Feedback
- duducheng/DenseSharp: [Cancer Research] 3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas
- M3DV/Kickstart: Study route for learners in machine learning / deep learning / computer vision
- duducheng/2048-api: Educational API for developing ML (imitation learning or reinforcement learning) agents to play game 2048
- duducheng/clustering_tutorial: A Tutorial of KMeans(++), GMM and Spectral Clustering
- M3DV/ai-deadlines: ⏰ top AI deadline countdowns (with an emphasis on computer vision and medical images)
- duducheng/Learning-Notes: Notes and resources on Machine Learning
- duducheng/deeplabv3p_gluon: DeepLab v3+ in MXNet Gluon
Total Stars: 2136. Total Forks: 473. Updated on December 27, 2024.