I am Yujian Liu, from China. I am a master’s graduate in Biomedical Engineering from South China University of Technology, advised by Prof. Shidang Xu. I also work as an algorithm intern at Beijing Yuaiweiwu Technology Co., Ltd. under Dr. Xiaoli Liu.

My research interests include:

  • High-fidelity 3D Gaussian avatars and speech-driven facial animation
  • Whole slide image (WSI) analysis and computational pathology
  • AI for drug discovery, including protein–ligand interaction prediction and molecular generation

I am currently applying to PhD programs for Spring/Fall 2027 admission. Prospective advisors and collaborators are welcome to reach out.

🎓 Education

💼 Experience

  • 2024.07 – Present, Algorithm Intern, Beijing Yuaiweiwu Technology Co., Ltd., Beijing, China
    Supervised by Dr. Xiaoli Liu.
  • 2026.07 – Present, Research Assistant, South China University of Technology, Guangzhou, China
    Supervised by Prof. Shidang Xu.

🔬 Research Projects

Fig. 1 E-CloudBind
Accepted by Nat. Commun. (JCR Q1, IF=18.1)

An electron-density point-cloud framework for robust protein–ligand interaction prediction

Yujian Liu*, Yutong Wang*, Qingquan Wang*, Meitang Peng, Yuan Chen, Yuechuan Lin, Dongxu Shen, Xiaoli Liu, Shidang Xu, Bin Liu

Predicts protein–ligand binding affinity from electron-density point clouds, remaining robust when atomic coordinates are noisy or come from predicted structures.

Details Paper Code

Fig. 1 AnyAvatar
Accepted by ACM MM

AnyAvatar: High-Fidelity Gaussian Head Avatars under Uncalibrated Camera Settings

Yujian Liu*, Dongxu Shen*, Haoran Li, Yuting Liu, Chuang Chen, Xinyi Jiang, Zhupeng Jiang, Peng Cao, Shidang Xu, Xiaoli Liu

Reconstructs animatable 3D Gaussian head avatars from uncalibrated multi-view images by jointly refining camera poses, FLAME geometry, and Gaussian appearance.

Details Project Code

Fig. 1 MPFusion-MIL
Accepted by ACM MM

MPFusion-MIL: Morphology-Guided Fusion with Precise Cross-Scale Interaction for Whole Slide Image Analysis

Yujian Liu, Ruoxuan Wu, Yuechuan Lin, Xinjie Shen, Yutong Wang, Haiyu Zhou, Shipu Xu, Shaoai Cai, Lingyu Liang, Shidang Xu

A multi-magnification MIL model that keeps spatial correspondence across scales and injects localized high-resolution evidence into aligned coarse regions.

Details

Fig. 1 PyraE2E
Accepted by ECCV

PyraE2E: Enhancing End-to-End WSI Analysis via Cross-Scale Super-Resolution

Yuechuan Lin*, Yujian Liu*, Weipeng Zhang, Yanyu Fan, Zikang Wang, Dongxu Shen, Liqin Fei, Xiaoli Liu, Shidang Xu

An end-to-end WSI framework that turns the slide resolution pyramid into cross-scale super-resolution supervision, so the encoder and aggregator can be trained together.

Details

Fig. 1 SyncAnimation
Accepted by IJCAI (Oral)

SyncAnimation: A Real-Time End-to-End Framework for Audio-Driven Human Pose and Talking Head Animation

Yujian Liu*, Shidang Xu*, Jing Guo, Dingbin Wang, Zairan Wang, Xianfeng Tan, Xiaoli Liu

A real-time NeRF talking avatar that jointly synthesizes audio-synchronized head pose, facial expression, and lip motion in one pipeline.

Details Poster Project Code arXiv

Fig. 1 CDSR
Accepted by PRCV

Minimal High-Resolution Patches Are Sufficient for Whole Slide Image Representation via Cascaded Dual-Scale Reconstruction

Yujian Liu*, Yuechuan Lin*, Dongxu Shen*, Haoran Li, Yutong Wang, Xiaoli Liu, Shidang Xu

Shows that a small set of informative high-resolution patches, selected and reconstructed through cascaded dual-scale learning, is sufficient for robust WSI representation.

Details Poster arXiv

Fig. 1 MoGaFace
Accepted by PRCV

MoGaFace: Momentum-Guided and Texture-Aware Gaussian Avatars for Consistent Facial Geometry

Yujian Liu, Linlang Cao, Chuang Chen, Fanyu Geng, Dongxu Shen, Peng Cao, Shidang Xu, Xiaoli Liu

Improves 3D Gaussian head avatars by jointly correcting facial geometry and recovering texture during rendering, instead of relying on a frozen tracked mesh.

Details Poster Project arXiv

Fig. 1 ML-Enhanced Nanoparticle Design
Accepted by Advanced Science (JCR Q1, IF=14.1)

Machine Learning-Enhanced Nanoparticle Design for Precision Cancer Drug Delivery

Qingquan Wang, Yujian Liu, Chenchen Li, Bin Xu, Shidang Xu, Bin Liu

Reviews how machine learning can guide nanoparticle synthesis and formulation, and help model nano–bio interactions along the cancer drug-delivery pipeline, from circulation and tumor extravasation to penetration and cellular uptake.

Paper

Fig. 1 Lipid Nanoparticles
Major Revision in Nat. Commun. (JCR Q1, IF=18.1)

Discovery of activable oncolytic ionizable lipid nanoparticles for selective cancer therapy

Hou-Bing Zhang*, Yujian Liu*, Weide Xu*, et al.

Uses machine-learning-accelerated screening to discover activable oncolytic ionizable lipid nanoparticles for selective cancer therapy.

Fig. 1 DXTalker
Submitted to AAAI

DXTalker: Factorizing Speech-Driven 3D Facial Animation via Articulatory Prototypes and Personalized Dynamics

Yujian Liu, Shidang Xu, Xiaoli Liu, et al.

Factorizes speech-driven 3D facial animation into shared articulatory prototypes and identity-specific dynamics for accurate lip sync and expressive motion.

🏆 Awards

  • 2022, Honorable Mention, Mathematical Contest in Modeling/Interdisciplinary Contest in Modeling
  • 2022, National Second Prize, Chinese Collegiate Computing Competition
  • 2022, National Third Prize, China College Student Service Outsourcing Innovation and Entrepreneurship Competition
  • 2022, National Third Prize, National College Student Market Survey and Analysis Competition
  • 2021, Meritorious Winner, Mathematical Contest in Modeling/Interdisciplinary Contest in Modeling
  • 2021, National Second Prize, Contemporary Undergraduate Mathematical Contest in Modeling