Rongzhi Dong - RankMe

17 papers Journal 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Foundation-Model Surrogates Enable Data-Efficient Active Learning for Materials Discovery. CoRR Jeffrey Hu, Rongzhi Dong, Ying Feng, Ming Hu, Jianjun Hu
2025	J	`jnl`	Facet: highly efficient E(3)-equivariant networks for interatomic potentials. CoRR Nicholas Miklaucic, Lai Wei, Rongzhi Dong, Nihang Fu, Sadman Sadeed Omee, Qingyang Li, Sourin Dey, Victor Fung, Jianjun Hu
2024	J	`jnl`	AlphaCrystal-II: Distance matrix based crystal structure prediction using deep learning. CoRR Yuqi Song, Rongzhi Dong, Lai Wei, Qin Li, Jianjun Hu
2024	J	`jnl`	Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study. CoRR Sadman Sadeed Omee, Nihang Fu, Rongzhi Dong, Ming Hu, Jianjun Hu
2023	J	`jnl`	Discovery of 2D Materials using Transformer Network-Based Generative Design. Adv. Intell. Syst. Rongzhi Dong, Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu
2023	J	`jnl`	Discovery of 2D materials using Transformer Network based Generative Design. CoRR Rongzhi Dong, Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu
2023	J	`jnl`	Generative Design of inorganic compounds using deep diffusion language models. CoRR Rongzhi Dong, Nihang Fu, Dirisuriya M. D. Siriwardane, Jianjun Hu
2023	J	`jnl`	Global Mapping of Structures and Properties of Crystal Materials. J. Chem. Inf. Model. Qinyang Li, Rongzhi Dong, Nihang Fu, Sadman Sadeed Omee, Lai Wei, Jianjun Hu
2023	J	`jnl`	Material transformers: deep learning language models for generative materials design. Mach. Learn. Sci. Technol. Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu
2022	J	`jnl`	Materials Property Prediction with Uncertainty Quantification: A Benchmark Study. CoRR Daniel Varivoda, Rongzhi Dong, Sadman Sadeed Omee, Jianjun Hu
2022	J	`jnl`	Materials Transformers Language Models for Generative Materials Design: a benchmark study. CoRR Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu
2022	J	`jnl`	Scalable deeper graph neural networks for high-performance materials property prediction. Patterns Sadman Sadeed Omee, Steph-Yves M. Louis, Nihang Fu, Lai Wei, Sourin Dey, Rongzhi Dong, Qinyang Li, Jianjun Hu
2021	J	`jnl`	Crystal structure prediction of materials with high symmetry using differential evolution. CoRR Wenhui Yang, Edirisuriya M. Dilanga Siriwardane, Rongzhi Dong, Yuxin Li, Jianjun Hu
2021	J	`jnl`	Scalable deeper graph neural networks for high-performance materials property prediction. CoRR Sadman Sadeed Omee, Steph-Yves M. Louis, Nihang Fu, Lai Wei, Sourin Dey, Rongzhi Dong, Qinyang Li, Jianjun Hu
2020	J	`jnl`	Computational Prediction of Critical Temperatures of Superconductors Based on Convolutional Gradient Boosting Decision Trees. IEEE Access Yabo Dan, Rongzhi Dong, Zhuo Cao, Xiang Li, Chengcheng Niu, Shaobo Li, Jianjun Hu
2020	J	`jnl`	Critical Temperature Prediction of Superconductors Based on Atomic Vectors and Deep Learning. Symmetry Shaobo Li, Yabo Dan, Xiang Li, Tiantian Hu, Rongzhi Dong, Zhuo Cao, Jianjun Hu
2019	J	`jnl`	Limited Data Rolling Bearing Fault Diagnosis With Few-Shot Learning. IEEE Access Ansi Zhang, Shaobo Li, Yuxin Cui, Wanli Yang, Rongzhi Dong, Jianjun Hu