Shikun Feng
Tsinghua University. BEIJING, P.R.China
Updated: I recently joined Zhongguancun Academy as an Assistant Professor and PhD supervisor. and I am currently recruiting PhD students. If you have already been admitted to Zhongguancun Academy and are interested in my research areas, please feel free to contact me via email at kunayumi@163.com or reach out to me directly on DingTalk.
My name is Shikun Feng, and I am a fourth-year PhD candidate in the Department of Computer Science at Tsinghua University, under the supervision of Professors Yanyan Lan and Wei-Ying Ma. My research interests include Multimodal Learning, Computer Vision, and AI for Science. Prior to pursuing my PhD, I worked as a senior computer vision algorithm engineer at SenseTime.
selected publications
- arXivStreamVTON: Bridging Multimodal Cognition and Diffusion Transformer for Streamlined End-to-End Video Virtual Try-OnarXiv preprint, 2026Co-first author; Corresponding author
- NeurIPS25FIGRDock: Fast Interaction-Guided Regression for Flexible Docking2025
- NeurIPS25Straight-Line Diffusion Model for Efficient 3D Molecular GenerationarXiv preprint arXiv:2503.02918, 2025
- ICLR25UniGEM: A Unified Approach to Generation and Property Prediction for MoleculesarXiv preprint arXiv:2410.10516, 2025
- ICML23Fractional denoising for 3d molecular pre-trainingIn International Conference on Machine Learning, 2023
- arXiv
- ICLR24Protein-ligand binding representation learning from fine-grained interactionsIn The Twelfth International Conference on Learning Representations, 2024
- ICML24UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation LearningIn Forty-first International Conference on Machine Learning, 2024
- Nat Mach IntellPre-training with fractional denoising to enhance molecular property predictionNature Machine Intelligence, 2024
- ICLR24Sliced Denoising: A Physics-Informed Molecular Pre-Training MethodIn The Twelfth International Conference on Learning Representations, 2024
- ICLR24Multimodal Molecular Pretraining via Modality BlendingIn The Twelfth International Conference on Learning Representations, 2024
- arXivMoleculeCLA: Rethinking Molecular Benchmark via Computational Ligand-Target Binding AnalysisarXiv preprint arXiv:2406.17797, 2024