News

• [2026.01] 🏆 Our team won ranked 6th overall, and ranked 1st among teams that didn’t use any extra molecular property data in OpenADMET – ExpansionRx Blind Challenge, the largest ADMET prediction competition to date!
• [2025.12] 🎉 Our work “Multimodal Out-of-Distribution Individual Uncertainty Quantification Enhances Binding Affinity Prediction for Polypharmacology” is accepted by Nature Machine Intelligence!
• [2025.07] 🎉 Our work “Learning Point Cloud Representations with Pose Continuity for Depth-Based Category-Level 6D Object Pose Estimation” is accepted by Recovering 6D Object Pose (R6D) Workshop at International Conference on Computer Vision (ICCV)!
• [2025.05] 🎉 Our US patent “Method and Apparatus for Designing Ligand Molecules” is published!
• [2024.06] 🎉 Our work “MolGene-E: Inverse Molecular Design to Modulate Single Cell Transcriptomics” is accepted by AI for Science Workshop at International Conference on Machine Learning (ICML)!
• [2023.10] 🎉 Our work “A Universal Framework for Accurate and Efficient Geometric Deep Learning of Molecular Systems” is accepted by Scientific Reports!
• [2023.10] 🎉 Our work “Protein Language Model-Powered 3-Dimensional Ligand Binding Site Prediction from Protein Sequence” is accepted by AI for Science Workshop at Neural Information Processing Systems (NeurIPS)!
• [2023.09] 🎓 I earned my Ph.D. in Computer Science from the Graduate Center, CUNY!
• [2023.01] 🎉 Our work “End-to-End Sequence-Structure-Function Meta-Learning Predicts Genome-Wide Chemical-Protein Interactions for Dark Proteins” is accepted by PLOS Computational Biology!