I am currently a CS/ML Ph.D student at {Mila - Quebec AI Institute, Université de Montréal} working with Jian Tang. Before that, I received my Bachelor’s degrees in Chemistry and Mathematics from Shanghai Jiao Tong University (Zhiyuan Honors Program) in 2021. I used to work as research intern at Bytedance {AI-Lab (Shanghai), Data-AML (Seattle)}. This summer (2025), I am joining the Apple - Machine Learning Research (MLR) at Cupertino, CA as Research Intern.
I am looking for full-time industry opportunities in the field of ML research starting from summer or fall 2026! Please reach out if you find me interesting!
[Contact Me]:
Google Scholar | Github | LinkedIn | X (twitter) | jiaruilu27 [at] gmail [dot] com
During my PhD, I develop 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. My work aims to bridge the gap between the learning methods and real-world applications, especially in the scientific domain.
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
Structure Language Models for Protein Conformation Generation.
Jiarui Lu, Xiaoyin Chen, Stephen Z. Lu, Chence Shi, Hongyu Guo, Yoshua Bengio, and Jian Tang.
The 13th 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 12th 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
Protein Sequence and Structure Co-design with Equivariant Translation.
Chence Shi, Chuanrui Wang, Jiarui Lu, Bozitao Zhong, and Jian Tang.
The 11th International Conference on Learning Representations (ICLR) 2023 | Code
“Artificial Intelligence for Protein Design.”
Tutorial at AAAI 2025, Feb. 26th, 2025 | Link | Slides
“Generative Conformation Sampling for Biomolecules.”
Guest Research Talk at ByteDance, Jun. 11th, 2024 | 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
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)
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.
Under review.
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
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
Structure Language Models for Protein Conformation Generation.
Jiarui Lu*, Xiaoyin Chen*, Stephen Z. Lu, Chence Shi, Hongyu Guo, Yoshua Bengio, and Jian Tang.
The 13th 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 12th 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 12th 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 11th 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)