Jiarui Lu 「卢家睿」

About

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 and Mathematics from Shanghai Jiao Tong University (Zhiyuan College) in 2021. He used to work as research intern at Apple - ML Research at Apple - ML Research (Cupertino) and ByteDance {AI-Lab (Shanghai), Data-AML (Seattle)}.

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Google Scholar | LinkedIn | X (twitter) | Github | jiaruilu27 _[at] gmail _[dot] com

Research Interest

Jiarui’s work aims to bridge the gap between the learning-based (AI) methods and real-world applications, especially in the scientific domain. During his PhD, he 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.

Selected Works

• 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