Jiarui is a CS/ML Ph.D student at {Mila - Quebec AI Institute, Université de Montréal} working with Jian Tang. Before that, He received the Bachelor’s degrees in {Chemistry, Mathematics} from Shanghai Jiao Tong University (Zhiyuan Honors Program) in 2021. He used to work as research intern at Apple - ML Research (Cupertino) and Bytedance {AI-Lab (Shanghai), Data-AML (Seattle)}.
[Contact Me]:
Google Scholar | Github | LinkedIn | X (twitter) | jiaruilu27 [at] gmail [dot] com
During his PhD, Jiarui develops machine learning (ML) methods to tackle fundamental scientific challenges, specializing in generative models that capture the intricate dynamics of biomolecular structures, which is key to understanding their biological functions. His work aims to bridge the gap between the learning methods and real-world applications, especially in the scientific domain.
SimpleFold: Folding Proteins is Simpler than You Think.
Yuyang Wang, Jiarui Lu, Navdeep Jaitly, Josh Susskind, and Miguel Angel Bautista.
The Fourteenth International Conference on Learning Representations (ICLR) 2026 | Code
Aligning Protein Conformation Ensemble Generation with Physical Feedback.
Jiarui Lu, Xiaoyin Chen, Stephen Z. Lu, Aurelie Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang.
Forty-second International Conference on Machine Learning (ICML) 2025 | Code
Structure Language Models for Protein Conformation Generation.
Jiarui Lu, Xiaoyin Chen, Stephen Z. Lu, Chence Shi, Hongyu Guo, Yoshua Bengio, and Jian Tang.
The Thirteenth International Conference on Learning Representations (ICLR) 2025 | Code
Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling.
Jiarui Lu, Bozitao Zhong, Zuobai Zhang, and Jian Tang.
The Twelfth International Conference on Learning Representations (ICLR) 2024 | Code
Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing.
Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang, Chaowei Xiao, and Anima Anandkumar.
Nature Machine Intelligence 5, no. 12 (2023): 1447-1457 | Code
“Artificial Intelligence for Protein Design.”
Tutorial at AAAI 2025, Feb. 26th, 2025 | Link | Slides
“Recent Advances of Generative Learning on Protein Structures.”
Guest Talk at {Department of Computer Science and Engineering, Institute of Natural Sciences}, Shanghai Jiao Tong University, Feb. {26th, 27th}, 2024 | Slides
SimpleDesign - A Joint Model for Protein Sequence and Structure Codesign.
Jiarui Lu, Yuyang Wang, Yizhe Zhang, Jiatao Gu, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista.
Under review (2026).
Learning Structure, Energy, and Dynamics: A Survey of Artificial Intelligence for Protein Dynamics.
Haocheng Tang, Liang Shi, Ya-Shi Zhang, Xixian Liu, Jian Tang, Jiarui Lu.
arXiv preprint arXiv:2604.25244 (2026)
Atomic Trajectory Modeling with State Space Models for Biomolecular Dynamics.
Liang Shi, Jiarui Lu, Junqi Liu, Chence Shi, Zhi Yang, Jian Tang.
arXiv preprint arXiv:2603.17633 (2026)
Self-Evolving Curriculum for LLM Reasoning.
Xiaoyin Chen, Jiarui Lu, Minsu Kim, Dinghuai Zhang, Jian Tang, Alexandre Piché, Nicolas Gontier, Yoshua Bengio and Ehsan Kamalloo.
arXiv preprint arXiv:2505.14970 (2025)
Reaction-conditioned De Novo Enzyme Design with GENzyme.
Chenqing Hua, Jiarui Lu, Yong Liu, Odin Zhang, Jian Tang, Rex Ying, Wengong Jin, Guy Wolf, Doina Precup, and Shuangjia Zheng.
arXiv preprint arXiv:2411.16694 (2024)
ProtIR: Iterative Refinement between Retrievers and Predictors for Protein Function Annotation.
Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie Lozano, Payel Das, and Jian Tang.
arXiv preprint arXiv:2402.07955 (2024)
Torchdrug: A powerful and flexible machine learning platform for drug discovery.
Zhaocheng Zhu, Chence Shi, Zuobai Zhang, Shengchao Liu, Minghao Xu, Xinyu Yuan, Yangtian Zhang, Junkun Chen, Huiyu Cai, Jiarui Lu, Chang Ma, Runcheng Liu, Louis-Pascal Xhonneux, Meng Qu, Jian Tang.
arXiv preprint arXiv:2202.08320 (2022) | Homepage
A text-guided protein design framework.
Shengchao Liu, Yanjing Li, Zhuoxinran Li, Anthony Gitter, Yutao Zhu, Jiarui Lu, Zhao Xu, Weili Nie, Arvind Ramanathan, Chaowei Xiao, Jian Tang, Hongyu Guo, and Anima Anandkumar.
Nature Machine Intelligence (2025): 1-12.
Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled.
Shengchao Liu, Chengpeng Wang, Jiarui Lu, Weili Nie, Hanchen Wang, Zhuoxinran Li, Bolei Zhou, and Jian Tang.
Transactions on Machine Learning Research (TMLR) 2024
Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing.
Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang, Chaowei Xiao, and Anima Anandkumar.
Nature Machine Intelligence 5, no. 12 (2023): 1447-1457
ReLMole: Molecular Representation Learning Based on Two-Level Graph Similarities.
Zewei Ji, Runhan Shi, Jiarui Lu, Fang Li, and Yang Yang.
Journal of Chemical Information and Modeling 62, no. 22 (2022): 5361-5372
EmbedDTI: Enhance the molecular representations via sequence embedding and GCN for the prediction of drug-target interaction.
Yuan Jin, Jiarui Lu, Runhan Shi, Yang Yang.
Biomolecules 11.12 (2021): 1783
KenDTI: An ensemble model for predicting drug-target interaction by integrating multi-source information.
Zhimiao Yu, Jiarui Lu, Yuan Jin, and Yang Yang.
IEEE/ACM Transactions on Computational Biology and Bioinformatics 18, no. 4 (2021): 1305-1314
Conditionally Site-Independent Neural Evolution of Antibody Sequences.
Stephen Zhewen Lu, Aakarsh Vermani, Kohei Sanno, Jiarui Lu, Frederick A Matsen, Milind Jagota, Yun S. Song.
Forty-third International Conference on Machine Learning (ICML) 2026
SimpleFold: Folding Proteins is Simpler than You Think.
Yuyang Wang, Jiarui Lu, Navdeep Jaitly, Josh Susskind, and Miguel Angel Bautista.
The Fourteenth International Conference on Learning Representations (ICLR) 2026 | Code
Efficient Regression-based Training of Normalizing Flows for Boltzmann Generators.
Danyal Rehman, Oscar Davis, Jiarui Lu, Jian Tang, Michael Bronstein, Yoshua Bengio, Alexander Tong, Avishek Joey Bose.
The Fourteenth International Conference on Learning Representations (ICLR) 2026
Measuring Scientific Capabilities of Language Models with a Systems Biology Dry Lab.
Haonan Duan, Stephen Zhewen Lu, Caitlin Fiona Harrigan, Nishkrit Desai, Jiarui Lu, Michał Koziarski, Leonardo Cotta and Chris J. Maddison.
NeurIPS 2025 Datasets and Benchmarks Track
Aligning Protein Conformation Ensemble Generation with Physical Feedback.
Jiarui Lu, Xiaoyin Chen, Stephen Z. Lu, Aurelie Lozano, Vijil Chenthamarakshan, Payel Das, Jian Tang.
Forty-second International Conference on Machine Learning (ICML) 2025
Towards Protein Sequence & Structure Co-Design with Multi-Modal Language Models.
Stephen Z. Lu, Jiarui Lu, Hongyu Guo, Jian Tang.
ICML 2025 Workshop LMRL
Fort: Forward-only regression training of normalizing flows.
Danyal Rehman, Oscar Davis, Jiarui Lu, Jian Tang, Michael M Bronstein, Yoshua Bengio, Alexander Tong, Joey Bose.
GenBio Workshop at ICML 2025 (Best Paper Award [Link])
Structure Language Models for Protein Conformation Generation.
Jiarui Lu, Xiaoyin Chen, Stephen Z. Lu, Chence Shi, Hongyu Guo, Yoshua Bengio, and Jian Tang.
The Thirteenth International Conference on Learning Representations (ICLR) 2025
Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations.
Jiarui Lu, Zuobai Zhang, Bozitao Zhong, Chence Shi, and Jian Tang.
GEM Bio Workshop at ICLR 2024
Structure-Informed Protein Language Model.
Zuobai Zhang, Jiarui Lu, Vijil Chenthamarakshan, Aurélie Lozano, Payel Das, and Jian Tang.
GEM Bio Workshop at ICLR 2024
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets.
Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michał Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters.
The Twelfth International Conference on Learning Representations (ICLR) 2024
Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling.
Jiarui Lu, Bozitao Zhong, Zuobai Zhang, and Jian Tang.
The Twelfth International Conference on Learning Representations (ICLR) 2024
Score-based Enhanced Sampling for Protein Molecular Dynamics.
Jiarui Lu, Bozitao Zhong, and Jian Tang.
ICML 2023 Workshop on SPIGM
Protein sequence and structure co-design with equivariant translation.
Chence Shi, Chuanrui Wang, Jiarui Lu, Bozitao Zhong, and Jian Tang.
The Eleventh International Conference on Learning Representations (ICLR) 2023
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding.
Minghao Xu, Zuobai Zhang, Jiarui Lu, Zhaocheng Zhu, Yangtian Zhang, Chang Ma, Runcheng Liu, and Jian Tang.
Advances in Neural Information Processing Systems 35, Track on Datasets and Benchmarks (NeurIPS 2022)