10.2025	I will give keynote talks at two workshops at ICCV 2025: 2nd Edition of Workshop on Foundation Models for V2X-Based Cooperative Autonomous Driving, 1st Workshop on Generating Digital Twins from Images and Videos.
08.2025	I joined the School of Data Science at the University of Virginia as a tenure-track Assistant Professor.
08.2025	I will serve as an Area Chair for CVPR 2026.
06.2025	Our work DiffuMatch: Category-Agnostic Spectral Diffusion Priors for Robust Non-rigid Shape Matching has been accepted by ICCV 2025.
06.2025	Our work MeshPad: Interactive Sketch-Conditioned Artist-Designed Mesh Generation and Editing has been accepted by ICCV 2025.
03.2025	I was invited to serve as a member of the program committee for Pacific Graphics 2025.
02.2025	Our work MeshArt: Generating Articulated Meshes with Structure-Guided Transformers has been accepted by CVPR 2025.
02.2025	Our work LT3SD: Latent Trees for 3D Scene Diffusion has been accepted by CVPR 2025.
12.2024	I was invited to serve as a member of the international program committee for Shape Modeling International 2025.
11.2024	I was invited to serve as a member of the international program committee for Eurographics Symposium on Geometry Processing 2025.
07.2024	Our work To Supervise or Not to Supervise: Understanding and Addressing the Key Challenges of Point Cloud Transfer Learning has been accepted by ECCV 2024.
06.2024	I was invited to serve as a member of the Full Papers International Program Committee for Eurographics 2025.
05.2024	I gave a talk, titled Empowering Machines with Deeper Shape Understanding, at the first CS Schnupperstudium Event for Women organized by Technical University of Munich.
02.2024	Our work GenZI: Zero-Shot 3D Human-Scene Interaction Generation has been accepted by CVPR 2024.
01.2024	I was invited to serve as a member of the Technical Papers Committee for Eurographics Symposium on Geometry Processing 2024.
07.2023	I gave an invited talk, titled Towards Robust Shape Correspondence: Learning with Receptive Field Optimization, in the Group of Geometric Computation and Visualisation led by Prof. Shengjun Liu at Central South University, China.
03.2023	Postdoc at 3D AI Lab, Technical University of Munich.
02.2023	Our work Generalizable Local Feature Pre-training for Deformable Shape Analysis has been accepted by CVPR 2023 and selected as a highlight (10% of accepted papers, 2.5% of submissions).
01.2023	I gave an invited talk, titled Towards Robust Geometric Deep Learning for Shape Correspondence, as part of the Dell Technical Generations Series Talk organized by Dell Technologies, Shanghai.
09.2022	I gave a poster presentation of our work SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence, at the first Hi! PARIS Meet Up event.
09.2022	Our work Learning Multi-resolution Functional Maps with Spectral Attention for Robust Shape Matching has been accepted by NeurIPS 2022.
08.2022	Our work SRFeat: Learning Locally Accurate and Globally Consistent Non-Rigid Shape Correspondence has been accepted by 3DV 2022.
03.2022	Our work WSDesc: Weakly Supervised 3D Local Descriptor Learning for Point Cloud Registration has been accepted by IEEE Transactions on Visualization and Computer Graphics.
03.2021	Our work PointDSC: Robust Point Cloud Registration Using Deep Spatial Consistency has been accepted by CVPR 2021.
11.2020	Postdoc at LIX, École Polytechnique / Inria.
10.2020	Our work Fast Sketch Segmentation and Labeling with Deep Learning is the runner-up for the 2019 Best Paper Award from IEEE Computer Graphics & Applications by the IEEE Computer Society Publications Board.
08.2020	Our work SketchDesc: Learning Local Sketch Descriptors for Multi-View Correspondence has been accepted by IEEE Transactions on Circuits and Systems for Video Technology.
06.2020	Ph.D. thesis defence.
05.2020	I gave an invited talk, titled End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds, at LIX, École Polytechnique / Inria.
04.2020	Our work Sketch-R2CNN: An RNN-Rasterization-CNN Architecture for Vector Sketch Recognition has been accepted by IEEE Transactions on Visualization and Computer Graphics.
02.2020	Our work End-to-End Learning Local Multi-View Descriptors for 3D Point Clouds has been accepted by CVPR 2020.
09.2019	Internship at Megvii Research. Advised by Dr. Jue Wang.
11.2018	Our work Fast Sketch Segmentation and Labeling with Deep Learning has been accepted by IEEE Computer Graphics & Applications.
08.2018	Our work Context-based Sketch Classification has been accepted by Expressive 2018.
06.2018	Internship at Alibaba A.I. Labs. Advised by Dr. Siyu Zhu and Prof. Ping Tan.
10.2016	Our work Model-driven Sketch Reconstruction with Structure-oriented Retrieval has been accepted by the ACM SIGGRAPH Asia 2016 Technical Briefs Program.