Selected first-author and co-first-author work; 16 peer-reviewed papers in total. Rui Ding is bolded; * denotes equal contribution. For the complete record including co-authored papers, see the CV or Google Scholar.
Text-Twin-Translation (T3): A Full-Stack Machine Learning Framework for Functional Material-Device Systems Discovery
Rui Ding*, Zixin Ding*, Rodrigo P. Ferreira*, Yuxin Chen, and Junhong Chen
Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '26), AI for Sciences Track, main conference (21% acceptance rate), pp. 10831–10841 (2026). Preliminary version selected for a Spotlight Oral at AI4Mat@ICLR 2026.
Spotlight Oral
ACM DL (doi:10.1145/3770855.3819013) · Plain-language summary · OpenReview · Code
Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts
Rui Ding, Jianguo Liu, Kang Hua, Xuebin Wang, Xiaoben Zhang, Minhua Shao, Yuxin Chen, and Junhong Chen
Science Advances 11, eadr9038 (2025)
DOI: 10.1126/sciadv.adr9038
Unlocking the Potential: Machine Learning Applications in Electrocatalyst Design for Electrochemical Hydrogen Energy Transformation
Rui Ding, Junhong Chen, Yuxin Chen, Jianguo Liu, Yoshio Bando, and Xuebin Wang
Chemical Society Reviews 53, 11390-11461 (2024)
Journal Cover
DOI: 10.1039/D4CS00844H
Expediting Field-Effect Transistor Chemical Sensor Design with Neuromorphic Spiking Graph Neural Networks
Rodrigo P. Ferreira*, Rui Ding*, Fengxue Zhang, Haihui Pu, Claire Donnat, Yuxin Chen, and Junhong Chen
Molecular Systems Design & Engineering 10, 345-356 (2025)
Journal Cover
DOI: 10.1039/D4ME00203B
Designing AI-Aided Analysis and Prediction Models for Nonprecious Metal Electrocatalyst-Based Proton Exchange Membrane Fuel Cells
Rui Ding, Ran Wang, Yiqin Ding, Wenjuan Yin, Yide Liu, Jia Li, and Jianguo Liu
Angewandte Chemie International Edition 59, 19175-19183 (2020)
DOI: 10.1002/anie.202006928
Unlocking New Insights for Electrocatalyst Design: A Unique Data Science Workflow Leveraging Internet-Sourced Big Data
Rui Ding, Xuebin Wang, Aidong Tan, Jia Li, and Jianguo Liu
ACS Catalysis 13, 13267-13281 (2023)
DOI: 10.1021/acscatal.3c01914
Machine Learning-Guided Discovery of Underlying Decisive Factors and New Mechanisms for the Design of Nonprecious Metal Electrocatalysts
Rui Ding, Yawen Chen, Ping Chen, Ran Wang, Jiankang Wang, Yiqin Ding, Wenjuan Yin, Yide Liu, Jia Li, and Jianguo Liu
ACS Catalysis 11, 9798-9808 (2021)
DOI: 10.1021/acscatal.1c01473
Applying Machine Learning to Boost the Development of High-Performance Membrane Electrode Assembly for Proton Exchange Membrane Fuel Cells
Rui Ding, Yiqin Ding, Hongyu Zhang, Ran Wang, Zihan Xu, Yide Liu, Wenjuan Yin, Jiankang Wang, Jia Li, and Jianguo Liu
Journal of Materials Chemistry A 9, 6841-6850 (2021)
Inside Cover
DOI: 10.1039/D0TA12571G
Inspecting Design Rules of Metal-Nitrogen-Carbon Catalysts for Electrochemical CO2 Reduction Reaction: From a Data Science Perspective
Rui Ding, Meng Ma, Yawen Chen, Xuebin Wang, Jia Li, Guoxiong Wang, and Jianguo Liu
Nano Research 16, 264-280 (2023)
DOI: 10.1007/s12274-022-4763-y
Machine Learning Utilized for the Development of Proton Exchange Membrane Electrolyzers
Rui Ding, Yawen Chen, Zhiyan Rui, Kang Hua, Yongkang Wu, Xiaoke Li, Xiao Duan, Jia Li, Xuebin Wang, and Jianguo Liu
Journal of Power Sources 556, 232389 (2023)
DOI: 10.1016/j.jpowsour.2022.232389
Guiding the Optimization of Membrane Electrode Assembly in a Proton Exchange Membrane Water Electrolyzer by Machine Learning Modeling and Black-Box Interpretation
Rui Ding, Yawen Chen, Zhiyan Rui, Kang Hua, Yongkang Wu, Xiaoke Li, Xiao Duan, Xuebin Wang, Jia Li, and Jianguo Liu
ACS Sustainable Chemistry & Engineering 10, 4561-4578 (2022)
DOI: 10.1021/acssuschemeng.1c08522
Application of Machine Learning in Optimizing Proton Exchange Membrane Fuel Cells: A Review
Rui Ding, Shiqiao Zhang, Yawen Chen, Zhiyan Rui, Kang Hua, Yongkang Wu, Xiaoke Li, Xiao Duan, Xuebin Wang, Jia Li, and Jianguo Liu
Energy and AI 9, 100170 (2022)
DOI: 10.1016/j.egyai.2022.100170
Effectively Increasing Pt Utilization Efficiency of the Membrane Electrode Assembly in Proton Exchange Membrane Fuel Cells through Multiparameter Optimization Guided by Machine Learning
Rui Ding*, Wenjuan Yin*, Gang Cheng, Yawen Chen, Jiankang Wang, Xuebin Wang, Min Han, Tianren Zhang, Yinliang Cao, Haimin Zhao, Shengping Wang, Jia Li, and Jianguo Liu
ACS Applied Materials & Interfaces 14, 8010-8024 (2022)
DOI: 10.1021/acsami.1c23221
Atomically Dispersed, Low-Coordinate Co-N Sites on Carbon Nanotubes as Inexpensive and Efficient Electrocatalysts for Hydrogen Evolution
Rui Ding, Yawen Chen, Xiaoke Li, Zhiyan Rui, Kang Hua, Yongkang Wu, Xiao Duan, Xuebin Wang, Jia Li, and Jianguo Liu
Small 18, 2105335 (2022)
DOI: 10.1002/smll.202105335
Boosting the Optimization of Membrane Electrode Assembly in Proton Exchange Membrane Fuel Cells Guided by Explainable Artificial Intelligence
Rui Ding*, Wenjuan Yin*, Gang Cheng, Yawen Chen, Jiankang Wang, Ran Wang, Zhiyan Rui, Jia Li, and Jianguo Liu
Energy and AI 5, 100098 (2021)
DOI: 10.1016/j.egyai.2021.100098
Facile Grafting Strategy Synthesis of Single-Atom Electrocatalyst with Enhanced ORR Performance
Rui Ding, Yide Liu, Zhiyan Rui, Jia Li, Jianguo Liu, and Zhigang Zou
Nano Research 13, 1519-1526 (2020)
Back Cover
DOI: 10.1007/s12274-020-2768-y
Geometry, Not Energy Surface, Drives the Neutral MLIP–DFT Gap in Atomistic Interaction Surrogates (RAPIDS)
Rui Ding*, Zixin Ding*, Rodrigo P. Ferreira*, Yuxin Chen, and Junhong Chen
AI4Physics, at ICML 2026
OpenReview
Hierarchical Deep Research with Local-Web RAG: Toward Automated System-Level Materials Discovery (DToR)
Rui Ding, Rodrigo P. Ferreira, Yuxin Chen, and Junhong Chen
arXiv preprint (2025); preliminary version at AI4Mat, at NeurIPS 2025
arXiv:2511.18303
Neuromorphic Random Walk for Experimental Phosphate Adsorption Modeling
Rodrigo P. Ferreira*, Rui Ding*, Rapti Ghosh, Haihui Pu, and Junhong Chen
Machine Learning and the Physical Sciences (ML4PS), at NeurIPS 2025
Paper (PDF)
From Laboratory Promise to Field Readiness: AI/ML for Discovering Water Materials That Survive Real Water
Rui Ding, Haihui Pu, Kuldip Kumar, Jonathan S. Grabowy, Dominic A. Brose, Maria Chan, Seth B. Darling, Andrew Ferguson, Yuxin Chen, and Junhong Chen
Under review at Nature Water
Hierarchical Deep Research with Local-Web RAG: Toward Automated System-Level Materials Discovery
Rui Ding, Peng Gong, Rodrigo P. Ferreira, Yuxin Chen, and Junhong Chen
Under review at Nature Machine Intelligence — extended manuscript
Reliability-Aware Routing for Foundation Atomistic Simulators in Non-Covalent Binding
Rui Ding, Zixin Ding, Rodrigo P. Ferreira, Yuxin Chen, and Junhong Chen
Under review at AAAI 2027 — extended manuscript
Nano-AI Convergence: Accelerating Materials Discovery and Overcoming Device Variability in Nanotechnology
Haihui Pu*, Rui Ding*, Tetyana Ignatova, Eric A. Josephs, Yuxin Chen, Wei Chen, and Junhong Chen
Under review at Digital Discovery
Toward Generalizable Device Twins from Million-Scale Scientific Literature Knowledge Graphs
Rui Ding et al.
In preparation
SciKGFM: Domain-Pretrained Foundation Models for Scientific Knowledge Graphs
Rui Ding et al.
In preparation