Near-Field Communication Sensors. - Zhonglin Cao; Ping Chen; Zhong Ma; Sheng Li; Xingxun Gao; Rui-xin Wu; Lijia Pan; Yi Shi (Sensors, 2019)

Deep Reinforcement Learning Optimizes Graphene Nanopores for Efficient Desalination. - Yuyang Wang 005; Zhonglin Cao; Amir Barati Farimani (CoRR, 2021)

MolCLR: Molecular Contrastive Learning of Representations via Graph Neural Networks. - Yuyang Wang 005; Jianren Wang; Zhonglin Cao; Amir Barati Farimani (CoRR, 2021)

Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy. - Junwoong Yoon; Zhonglin Cao; Rajesh K. Raju; Yuyang Wang 005; Robert Burnley; Andrew J. Gellman; Amir Barati Farimani; Zachary W. Ulissi (Mach. Learn. Sci. Technol., 2021)

MOFormer: Self-Supervised Transformer model for Metal-Organic Framework Property Prediction. - Zhonglin Cao; Rishikesh Magar; Yuyang Wang 005; Amir Barati Farimani (CoRR, 2022)

Molecular contrastive learning of representations via graph neural networks. - Yuyang Wang 005; Jianren Wang; Zhonglin Cao; Amir Barati Farimani (Nat. Mach. Intell., 2022)

Neural Network Predicts Ion Concentration Profiles under Nanoconfinement. - Zhonglin Cao; Yuyang Wang 005; Cooper Lorsung; Amir Barati Farimani (CoRR, 2023)

Large-scale Pretraining Improves Sample Efficiency of Active Learning based Molecule Virtual Screening. - Zhonglin Cao; Simone Sciabola; Ye Wang 024 (CoRR, 2023)

EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants. - Allan dos Santos Costa; Ilan Mitnikov; Franco Pellegrini; Ameya Daigavane; Mario Geiger; Zhonglin Cao; Karsten Kreis; Tess E. Smidt; Emine Küçükbenli; Joseph Jacobson (CoRR, 2024)

BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery. - Peter St. John; Dejun Lin; Polina Binder; Malcolm Greaves; Vega Shah; John St. John; Adrian Lange; Patrick D. Hsu; Rajesh Illango; Arvind Ramanathan; Anima Anandkumar; David H. Brookes; et al. (CoRR, 2024)

Large-Scale Pretraining Improves Sample Efficiency of Active Learning-Based Virtual Screening. - Zhonglin Cao; Simone Sciabola; Ye Wang 024 (J. Chem. Inf. Model., 2024)

Proteina: Scaling Flow-based Protein Structure Generative Models. - Tomas Geffner; Kieran Didi; Zuobai Zhang; Danny Reidenbach; Zhonglin Cao; Jason Yim; Mario Geiger; Christian Dallago; Emine Küçükbenli; Arash Vahdat; Karsten Kreis (ICLR, 2025)

A Deep-Learning-Based Targeted Interpolation Method for Seismic Data: A Consecutively Missing Trace VSP Case. - Wen Yang; Qianggong Song; Le Li; Xiaobin Li; Zhonglin Cao; Pengfei Duan (IEEE Geosci. Remote. Sens. Lett., 2025)

La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching. - Tomas Geffner; Kieran Didi; Zhonglin Cao; Danny Reidenbach; Zuobai Zhang; Christian Dallago; Emine Küçükbenli; Karsten Kreis; Arash Vahdat (CoRR, 2025)

Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow. - Zhonglin Cao; Mario Geiger; Allan dos Santos Costa; Danny Reidenbach; Karsten Kreis; Tomas Geffner; Franco Pellegrini; Guoqing Zhou; Emine Küçükbenli (CoRR, 2025)