Martin Saveski

Bio

I am a forth-year Ph.D. candidate (2021~) at Zhejiang University and Westlake University, advised by Stan Z. Li. My research focuses on generative AI for Science and focuses on solving key problems in the field of science, such as biomolecular design and spatiotemporal predictive learning.

Looking forward to academic communications and feel free to contact me!

News

[2024/09] Three co-first papers are accepted by NeurIPS 2024.
[2024/09] One paper is accepted by TNNLS.
[2024/07] One paper is accepted by NCAA.
[2024/07] One first author paper on, Multimodal Chain-of-Thought, is accepted by ECCV 2024.
[2024/05] One paper is accepted by ECML 2024.
[2024/05] One first author paper on, RNA secondary structure prediction, is accepted by ICML 2024.
[2024/02] Two co-authored papers are accepted by CVPR 2024.
[2024/01] One co-authored paper is accepted by TKDE.
[2024/01] Two first/co-first author papers on, RNA design and protein design, are accepted by ICLR 2024.
[2023/12] One paper is accepted by ICASSP 2023.
[2023/12] One first author paper on, Antibody design, is accepted by AAAI 2024.
[2023/10] I have been honored with the National Scholarship.
[2023/09] Four papers are accepted by NeurIPS 2023.
[2023/07] One paper is accepted by ACM MM 2023.
[2023/06] One paper is accepted by TKDE.
[2023/06] Three papers are accepted by ECML 2023.
[2023/04] One paper is accepted by Communications Biology.
[2023/03] One paper is accepted by TNNLS.
[2023/02] Two papers are accepted by CVPR 2023.
[2023/02] Three papers are accepted by ICASSP 2023.
[2023/01] Two papers are accepted by ICLR 2023.
[2022/06] One paper is accepted by ECML 2022.
[2022/03] Two papers are accepted by CVPR 2022.
[2022/02] One paper is accepted by ICASSP 2022.
[2022/01] One paper is accepted by NCAA.
[2021/11] One paper is accepted by TKDE.
[2021/08] One paper is accepted by ACM MM 2021.

Publications

Most recent publications on Google Scholar.
^‡ indicates equal contribution.

Selected
All

Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure

Bozhen Hu^‡, Cheng Tan^‡, Jun Xia, Yue Liu, Lirong Wu, Jiangbin Zheng, Yongjie Xu, Yufei Huang, Stan Z. Li

NeurIPS, 2024.

ProtGO: Function-Guided Protein Modeling for Unified Representation Learning

Bozhen Hu^‡, Cheng Tan^‡, Yongjie Xu, Zhangyang Gao, Jun Xia, Lirong Wu, Stan Z. Li

NeurIPS, 2024.

UniIF: Unified Molecule Inverse Folding

Zhangyang Gao^‡, Jue Wang^‡, Cheng Tan^‡, Lirong Wu, Yufei Huang, Siyuan Li, Zhirui Ye, Stan Z. Li

NeurIPS, 2024.

RFold: Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching Perspective

Cheng Tan^‡, Zhangyang Gao^‡, Hanqun Cao, Xingran Chen, Ge Wang, Lirong Wu, Jun Xia, Jiangbin Zheng, Stan Z. Li

ICML, 2024.

Paper Code

A Survey on Generative Diffusion Model

Hanqun Cao^‡, Cheng Tan^‡, Zhangyang Gao^‡, Yilun Xu, Guangyong Chen, Pheng-Ann Heng, Stan Z. Li

TKDE: IEEE Transactions on Knowledge and Data Engineering, 2024.

Paper Code

RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design

Cheng Tan^‡, Yijie Zhang^‡, Zhangyang Gao^‡, Bozhen Hu, Siyuan Li, Zicheng Liu, Stan Z. Li

ICLR, 2024.

Paper Code

KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement

Zhangyang Gao^‡, Cheng Tan^‡, Xingran Chen, Yijie Zhang, Jun Xia, Siyuan Li, Stan Z. Li

ICLR, 2024.

Paper Code

Cross-Gate MLP with Protein Complex Invariant Embedding is A One-Shot Antibody Designer

Cheng Tan^‡, Zhangyang Gao^‡, Lirong Wu, Jun Xia, Jiangbin Zheng, Xihong Yang, Yue Liu, Bozhen Hu, Stan Z. Li

AAAI, 2024.

Paper Code

OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning

Cheng Tan^‡, Siyuan Li^‡, Zhangyang Gao, Wenfei Guan, Zedong Wang, Zicheng Liu, Lirong Wu, Stan Z. Li

NeurIPS, 2023.

Paper Code

Proteininvbench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics

Zhangyang Gao^‡, Cheng Tan^‡, Yijie Zhang, Xingran Chen, Lirong Wu, Stan Z. Li

NeurIPS, 2023.

Paper Code

CONVERT: Contrastive Graph Clustering with Reliable Augmentation

Xihong Yang, Cheng Tan, Yue Liu, Ke Liang, Siwei Wang, Sihang Zhou, Jun Xia, Stan Z. Li, Xinwang Liu, En Zhu

ACM MM, 2023.

Paper Code

Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning

Cheng Tan^‡, Zhangyang Gao^‡, Lirong Wu, Yongjie Xu, Jun Xia, Siyuan Li, Stan Z. Li

CVPR, 2023.

Paper Code

PiFold: Toward Effective and Efficient Protein Inverse Folding

Zhangyang Gao^‡, Cheng Tan^‡, Stan Z. Li

ICLR, 2023 (Spotlight).

Paper Code

Hyperspherical Consistency Regularization

Cheng Tan^‡, Zhangyang Gao^‡, Lirong Wu, Siyuan Li, Stan Z. Li

CVPR, 2022.

Paper Code

SimVP: Simpler yet Better Video Prediction

Zhangyang Gao^‡, Cheng Tan^‡, Lirong Wu, Stan Z. Li

CVPR, 2022.

Paper Code

Co-learning: Learning from Noisy Labels with Self-supervision

Cheng Tan, Jun Xia, Lirong Wu, Stan Z. Li

ACM MM, 2021 (Oral).

Paper Code

Self-supervised Learning on Graphs: Contrastive, Generative, or Predictive

Lirong Wu, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li

TKDE: IEEE Transactions on Knowledge and Data Engineering, 2021.

Paper Code

Interpretable and Generalizable Spatiotemporal Predictive Learning with Disentangled Consistency

Jingxuan Wei^‡, Cheng Tan^‡, Zhangyang Gao, Linzhuang Sun, Bihui Yu, Ruifeng Guo, Stan Z. Li

ECML-PKDD, 2024.

Target-aware Molecular Graph Generation

Cheng Tan^‡, Zhangyang Gao^‡, Stan Z. Li

ECML-PKDD, 2023.

Paper Code

Learning to Augment Graph Structure for both Homophily and Heterophily Graphs

Lirong Wu^‡, Cheng Tan^‡, Zihan Liu, Zhangyang Gao, Haitao Lin, Stan Z. Li

ECML-PKDD, 2023.

Paper Code

CoSP: Co-supervised Pre-training of pocket and ligand

Zhangyang Gao^‡, Cheng Tan^‡, Jun Xia, Stan Z. Li

ECML-PKDD, 2023.

Paper Code

Generative De Novo Protein Design with Global Context

Cheng Tan^‡, Zhangyang Gao^‡, Jun Xia, Bozhen Hu, Stan Z. Li

ICASSP, 2023.

Paper Code

OT Cleaner: Label Correction as Optimal Transport

Jun Xia^‡, Cheng Tan^‡, Lirong Wu, Yongjie Xu, Stan Z. Li

ICASSP, 2022.

Paper Code

Structure-Preserving and Batch-Correcting Visualization Using Deep Manifold Transformation for Single-cell RNA-Seq Profiles

Yongjie Xu, Zelin Zang, Jun Xia, Cheng Tan, Yulan Geng, Stan Z Li

Communication Biology, 2023.

Paper Code

Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure

Bozhen Hu^‡, Cheng Tan^‡, Jun Xia, Yue Liu, Lirong Wu, Jiangbin Zheng, Yongjie Xu, Yufei Huang, Stan Z. Li

NeurIPS, 2024.

ProtGO: Function-Guided Protein Modeling for Unified Representation Learning

Bozhen Hu^‡, Cheng Tan^‡, Yongjie Xu, Zhangyang Gao, Jun Xia, Lirong Wu, Stan Z. Li

NeurIPS, 2024.

UniIF: Unified Molecule Inverse Folding

Zhangyang Gao^‡, Jue Wang^‡, Cheng Tan^‡, Lirong Wu, Yufei Huang, Siyuan Li, Zhirui Ye, Stan Z. Li

NeurIPS, 2024.

Towards Robust mph{De Novo} Peptide Sequencing in Proteomics against Data Biases

Jun Xia, Shaorong Chen, Jingbo Zhou, Xiaojun Shan, Wenjie Du, Zhangyang Gao, Cheng Tan, Bozhen Hu, Jiangbin Zheng, Stan Z. Li

NeurIPS, 2024.

RFold: Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching Perspective

Cheng Tan^‡, Zhangyang Gao^‡, Hanqun Cao, Xingran Chen, Ge Wang, Lirong Wu, Jun Xia, Jiangbin Zheng, Stan Z. Li

ICML, 2024.

Paper Code

A Graph is Worth K Words: Euclideanizing Graph using Pure Transformer

Zhangyang Gao, Daize Dong, Cheng Tan, Jun Xia, Bozhen Hu, Stan Z. Li

ICML, 2024.

Code

Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge

Yufei Huang, Odin Zhang, Lirong Wu, Cheng Tan, Haitao Lin, Zhangyang Gao, Siyuan Li, Stan Z. Li

ICML, 2024.

VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling

Siyuan Li, Zedong Wang, Zicheng Liu, Di Wu, Cheng Tan, Jiangbin Zheng, Yufei Huang, Stan Z. Li

ICML, 2024.

General Point Model Pretraining with Autoencoding and Autoregressive

Zhe Li, Zhangyang Gao, Cheng Tan, Bocheng Ren, Laurence Tianruo Yang, Stan Z. Li

CVPR, 2024

MLIP: Enhancing Medical Visual Representation with Divergence Encoder and Knowledge-guided Contrastive Learning

Zhe Li, Laurence Tianruo Yang, Bocheng Ren, Xin Nie Nie, Zhangyang Gao, Cheng Tan, Stan Z. Li

CVPR, 2024

A Survey on Generative Diffusion Model

Hanqun Cao^‡, Cheng Tan^‡, Zhangyang Gao^‡, Yilun Xu, Guangyong Chen, Pheng-Ann Heng, Stan Z. Li

TKDE: IEEE Transactions on Knowledge and Data Engineering, 2024.

Paper Code

RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design

Cheng Tan^‡, Yijie Zhang^‡, Zhangyang Gao^‡, Bozhen Hu, Siyuan Li, Zicheng Liu, Stan Z. Li

ICLR, 2024.

Paper Code

KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement

Zhangyang Gao^‡, Cheng Tan^‡, Xingran Chen, Yijie Zhang, Jun Xia, Siyuan Li, Stan Z. Li

ICLR, 2024.

Paper Code

SemiReward: A General Reward Model for Semi-supervised Learning

Siyuan Li, Weiyang Jin, Zedong Wang, Fang Wu, Zicheng Liu, Cheng Tan, Stan Z. Li

ICLR, 2024.

Code

MogaNet: Multi-order Gated Aggregation Network

Siyuan Li, Zedong Wang, Zicheng Liu, Cheng Tan, Haitao Lin, Di Wu, Zhiyuan Chen, Jiangbin Zheng, Stan Z. Li

ICLR, 2024.

Code

Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks

Tianyu Fan, Lirong Wu, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li

ICLR, 2024.

Cross-Gate MLP with Protein Complex Invariant Embedding is A One-Shot Antibody Designer

Cheng Tan^‡, Zhangyang Gao^‡, Lirong Wu, Jun Xia, Jiangbin Zheng, Xihong Yang, Yue Liu, Bozhen Hu, Stan Z. Li

AAAI, 2024.

Paper Code

PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction

Lirong Wu, Yufei Huang, Cheng Tan, Zhangyang Gao, Bozhen Hu, Haitao Lin, Zicheng Liu, Stan Z. Li

AAAI, 2024.

Wavelet-Driven Spatiotemporal Predictive Learning: Bridging Frequency and Time Variations

Xuesong Nie, Yunfeng Yan, Siyuan Li, Cheng Tan, Xi Chen, Haoyuan Jin, Zhihang Zhu, Stan Z. Li, Donglian Qi.

AAAI, 2024.

OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning

Cheng Tan^‡, Siyuan Li^‡, Zhangyang Gao, Wenfei Guan, Zedong Wang, Zicheng Liu, Lirong Wu, Stan Z. Li

NeurIPS, 2023.

Paper Code

Proteininvbench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics

Zhangyang Gao^‡, Cheng Tan^‡, Yijie Zhang, Xingran Chen, Lirong Wu, Stan Z. Li

NeurIPS, 2023.

Paper Code

Harnessing Hard Mixed Samples with Decoupled Regularizer

Zicheng Liu^‡, Siyuan Li^‡, Ge Wang, Lirong Wu, Cheng Tan, Stan Z. Li

NeurIPS, 2023.

Paper Code

Understanding the Limitations of Deep Models for Molecular property prediction: Insights and Solutions

Jun Xia, Lecheng Zhang, Xiao Zhu, Yue Liu, Zhangyang Gao, Bozhen Hu, Cheng Tan, Jiangbin Zheng, Siyuan Li, Stan Z. Li

NeurIPS, 2023.

Paper

CONVERT: Contrastive Graph Clustering with Reliable Augmentation

Xihong Yang, Cheng Tan, Yue Liu, Ke Liang, Siwei Wang, Sihang Zhou, Jun Xia, Stan Z. Li, Xinwang Liu, En Zhu

ACM MM, 2023.

Paper Code

GNN Cleaner: Label Cleaner for Graph Structured Data

Jun Xia, Haitao Lin, Yongjie Xu, Cheng Tan, Lirong Wu, Yongjie Xu, Siyuan Li, Stan Z. Li

TKDE: IEEE Transactions on Knowledge and Data Engineering, 2023.

Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning

Cheng Tan^‡, Zhangyang Gao^‡, Lirong Wu, Yongjie Xu, Jun Xia, Siyuan Li, Stan Z. Li

CVPR, 2023.

Paper Code

CVT-SLR: Contrastive Visual-Textual Transformation for Sign Language Recognition with Variational Alignment

Jiangbin Zheng, Yile Wang, Cheng Tan, Siyuan Li, Ge Wang, Jun Xia, Yidong Chen, Stan Z. Li

CVPR, 2023.

Paper Code

PiFold: Toward Effective and Efficient Protein Inverse Folding

Zhangyang Gao^‡, Cheng Tan^‡, Stan Z. Li

ICLR, 2023 (Spotlight).

Paper Code

Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules

Jun Xia, Chengshuai Zhao, Bozhen Hu, Zhangyang Gao, Cheng Tan, Yue Liu, Siyuan Li, Stan Z. Li

ICLR, 2023.

Paper Code

Hyperspherical Consistency Regularization

Cheng Tan^‡, Zhangyang Gao^‡, Lirong Wu, Siyuan Li, Stan Z. Li

CVPR, 2022.

Paper Code

SimVP: Simpler yet Better Video Prediction

Zhangyang Gao^‡, Cheng Tan^‡, Lirong Wu, Stan Z. Li

CVPR, 2022.

Paper Code

Co-learning: Learning from Noisy Labels with Self-supervision

Cheng Tan, Jun Xia, Lirong Wu, Stan Z. Li

ACM MM, 2021 (Oral).

Paper Code

Self-supervised Learning on Graphs: Contrastive, Generative, or Predictive

Lirong Wu, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li

TKDE: IEEE Transactions on Knowledge and Data Engineering, 2021.

Paper Code

Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting

Lirong Wu, Haitao Lin, Guojiang Zhao, Cheng Tan, Stan Z. Li

TNNLS: IEEE Transactions on Neural Networks and Learning Systems, 2024.

Paper Code

Enhancing Human-like Multi-Modal Reasoning: A New Challenging Dataset and Comprehensive Framework

Jingxuan Wei, Cheng Tan, Zhangyang Gao, Linzhuang Sun, Siyuan Li, Bihui Yu, Ruifeng Guo, Stan Z. Li

NCAA: Neural Computing and Applications, 2024.

Paper Code

Interpretable and Generalizable Spatiotemporal Predictive Learning with Disentangled Consistency

Jingxuan Wei^‡, Cheng Tan^‡, Zhangyang Gao, Linzhuang Sun, Bihui Yu, Ruifeng Guo, Stan Z. Li

ECML-PKDD, 2024.

Deep Manifold Transformation for Protein Representation Learning

Bozhen Hu, Zelin Zang, Cheng Tan, Stan Z. Li

ICASSP, 2024.

Target-aware Molecular Graph Generation

Cheng Tan^‡, Zhangyang Gao^‡, Stan Z. Li

ECML-PKDD, 2023.

Paper Code

Learning to Augment Graph Structure for both Homophily and Heterophily Graphs

Lirong Wu^‡, Cheng Tan^‡, Zihan Liu, Zhangyang Gao, Haitao Lin, Stan Z. Li

ECML-PKDD, 2023.

Paper Code

CoSP: Co-supervised Pre-training of pocket and ligand

Zhangyang Gao^‡, Cheng Tan^‡, Jun Xia, Stan Z. Li

ECML-PKDD, 2023.

Paper Code

Generative De Novo Protein Design with Global Context

Cheng Tan^‡, Zhangyang Gao^‡, Jun Xia, Bozhen Hu, Stan Z. Li

ICASSP, 2023.

Paper Code

Deep Manifold Graph Auto-Encoder for Attributed Graph Embedding

Bozhen Hu, Zelin Zang, Jun Xia, Lirong Wu, Cheng Tan, Stan Z. Li

ICASSP, 2023.

Paper

WordReg: Mitigating the Gap between Training and Inference with Worst-case Drop Regularization

Jun Xia, Ge Wang, Bozhen Hu, Cheng Tan, Jiangbin Zheng, Yongjie Xu, Stan Z. Li

ICASSP, 2023.

Paper

OT Cleaner: Label Correction as Optimal Transport

Jun Xia^‡, Cheng Tan^‡, Lirong Wu, Yongjie Xu, Stan Z. Li

ICASSP, 2022.

Paper Code

Beyond Homophily and Homogeneity Assumption: Relation-based Frequency Adaptive Graph Neural Networks

Lirong Wu, Haitao Lin, Bozhen Hu, Zhangyang Gao, Cheng Tan, Zicheng Liu, Stan Z. Li

TNNLS: IEEE Transactions on Neural Networks and Learning Systems, 2022.

Code

GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Context Prediction

Lirong Wu, Jun Xia, Zhangyang Gao, Haitao Lin, Cheng Tan, Stan Z. Li

ECML-PKDD, 2022.

Paper Code

Multi-level disentanglement graph neural network

Lirong Wu, Haitao Lin, Jun Xia, Cheng Tan, Stan Z. Li

NCAA: Neural Computing and Applications, 2022.

Paper Code

Structure-Preserving and Batch-Correcting Visualization Using Deep Manifold Transformation for Single-cell RNA-Seq Profiles

Yongjie Xu, Zelin Zang, Jun Xia, Cheng Tan, Yulan Geng, Stan Z Li

Communication Biology, 2023.

Paper Code

Service

Conference - Program committee member:

ICML, NeurIPS, ICLR, CVPR, ECCV, ICCV, AAAI, ACL, EMNLP, ACM MM, ECML-PKDD, ICASSP, etc.

Journal - Reviewer:

IEEE TPAMI - Transactions on Pattern Analysis and Machine Intelligence
IEEE TIP - Transactions on Image Processing
IEEE TCSVT - Transactions on Circuits and Systems for Video Technology
IEEE TNNLS - Transactions on Neural Networks and Learning Systems
Pattern Recognition
EAAI - Engineering Applications of Artificial Intelligence

Talks

2023/11/16: Talk on "Spatiotemporal Modeling and Its Applications on Weather Forecasting" @ Microsoft Suzhou.
2023/11/29: Talk on "OpenSTL Applications" @ Inner Mongolia Meteorological Service.

Awards and Honors

2023/10: National Scholarship.
2023/12: AAAI-24 Scholarship Award.
2024/03: ICLR 2024 Financial Assistance.
2024/06: ICML 2024 Financial Aid.

Vitæ

Zhejiang University Sept 2021 - present

Ph.D. Student
Computer Science and Technology
Westlake University Sept 2021 - present

Ph.D. Student
Computer Science and Technology
Tecent AI Lab Oct 2023 - Oct 2024

Research on Controllable Protein Design
Supervisor: Dr. Fandi Wu
University of Alberta, Canada. July 2019 - Oct 2019

Research Assistant
Artificial General Intelligence Lab
Prof. Vadim Bulitko (Professor, Computer Science)
Prof. Erin Bayne (Professor, Biology)
Northwest A&F University Sept 2017 - June 2021

B.Sc. Student
Computer Science and Technology

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