Youzhi Luo, Ph.D. candidate Department of Computer Science & Engineering Texas A&M University 364 L.F. Peterson Building 435 Nagle Street College Station, TX 77843 E-mail: yzluo@tamu.edu Google Scholar

Short Biography

I received my B.E. in Automation in 2019 from University of Science and Technology of China. I am currently a Ph.D. candidate in Department of Computer Science & Engineering, Texas A&M University. My advisor is Dr. Shuiwang Ji.

Education

• Ph.D., Computer Science, Texas A&M University, September 2019 - May 2024 (Expected)

• B.E., Automation, University of Science and Technology of China, September 2015 - July 2019

Research Interests

• Machine Learning

• Graph Neural Networks

• Deep Generative Models

• AI for Science

Preprints

• Xuan Zhang*, Limei Wang*, Jacob Helwig*, Youzhi Luo*, Cong Fu*, Yaochen Xie*, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, YuQing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stark, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alan Aspuru-Guzik, Erik Bekkers, Michael Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Lio, Rose Yu, Stephan Gunnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess Smidt, and Shuiwang Ji (* equal contribution)
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
arXiv: 2307.08423, 2023
• Youzhi Luo, Nathanael Yoder, Sercan Arik, Chen-Yu Lee, Tomas Pfister, Shuiwang Ji, Rose Yu
Editable Temporal Graph Neural Network for Interactive Time Series Forecasting
OpenReview, 2023
• Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization
arXiv: 2306.08076, 2023

Publications

• Zhao Xu, Yaochen Xie, Youzhi Luo, Xuan Zhang, Xinyi Xu, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji
3D Molecular Geometry Analysis with 2D Graphs
SIAM International Conference on Data Mining (SDM), 2024
• Youzhi Luo, Chengkai Liu, Shuiwang Ji
Towards Symmetry-Aware Generation of Periodic Materials
The 37th Conference on Neural Information Processing Systems (NeurIPS), Spotlight, 2023
• Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules
The 37th Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, 2023
• Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization
The 37th Conference on Neural Information Processing Systems (NeurIPS), 2023
• Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, and Shuiwang Ji
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction
The 40th International Conference on Machine Learning (ICML), 2023
• Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou.
Learning Fair Graph Representations via Automated Data Augmentations
The 11th International Conference on Learning Representations (ICLR), 2023
• Youzhi Luo, Michael McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji
Automated Data Augmentations for Graph Classification
The 11th International Conference on Learning Representations (ICLR), 2023
• Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, and Shuiwang Ji
  
Generating 3D Molecules for Target Protein Binding
The 39th International Conference on Machine Learning (ICML), Long Talk, 2022
• Youzhi Luo, and Shuiwang Ji
  
An Autoregressive Flow Model for 3D Molecular Geometry Generation
The 10th International Conference on Learning Representations (ICLR), 2022
• Zhengyang Wang*, Meng Liu*, Youzhi Luo*, Zhao Xu*, Yaochen Xie*, Limei Wang*, Lei Cai*, and Shuiwang Ji (* equal contribution)
  
Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery
Bioinformatics, 2022
• Meng Liu*, Youzhi Luo*, Limei Wang*, Yaochen Xie*, Hao Yuan*, Shurui Gui*, Haiyang Yu*, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora Oztekin, Xuan Zhang, and Shuiwang Ji (* equal contribution)
  
DIG: A Turnkey Library for Diving into Graph Deep Learning Research
Journal of Machine Learning Research (JMLR), 2021
• Qi Qi*, Youzhi Luo*, Zhao Xu*, Shuiwang Ji, and Tianbao Yang (* equal contribution)
  
Stochastic Optimization of Area Under Precision-Recall Curve for Deep Learning with Provable Convergence
The 35th Conference on Neural Information Processing Systems (NeurIPS), 2021
• Meng Liu, Cong Fu, Xuan Zhang, Limei Wang, Yaochen Xie, Hao Yuan, Youzhi Luo, Zhao Xu, Shenglong Xu, Shuiwang Ji
Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks
NeurIPS 2021 AI for Science Workshop, 2021
• Youzhi Luo, Keqiang Yan, and Shuiwang Ji
  
GraphDF: A Discrete Flow Model for Molecular Graph Generation
The 38th International Conference on Machine Learning (ICML), 2021

Services

Conference Reviewer

• ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020, 2023

• International Conference on Learning Representations (ICLR), 2022, 2023, 2024

• International Conference on Machine Learning (ICML), 2022, 2023

• Conference on Neural Information Processing Systems (NeurIPS), 2022, 2023

• AAAI Conference on Artificial Intelligence (AAAI), 2022, 2023

• Learning on Graphs Conference (LOGS), 2022, 2023

Journal Reviewer

• IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

Teaching

Guest Lecturer

• Attention Mechanism, CSCE 636: Deep Learning, Texas A&M University, Fall 2021, Fall 2022

• Attention Mechanism, BMI 6334: Deep Learning in Biomedical Informatics, UTHealth School of Biomedical Informatics, Fall 2021