Publications

Natalie Maus, Yimeng Zeng, Haydn Thomas Jones, Yining (Sam) Huang, Gaurav Ng Goel, Alden Rose, Kyurae Kim, Hyun-Su Lee, Marcelo Der Torossian Torres, Fangping Wan, Cesar de la Fuente-Nunez, Mark Yatskar, Osbert Bastani, Jacob R. Gardner (2026). Purely Agentic Black-Box Optimization for Biological Design. arXiv.
Paper
Felix Teufel, Aaron W Kollasch, Yining (Sam) Huang, Ole Winther, Kevin K Yang, Pascal Notin, Debora Marks (2025). Few-shot Protein Fitness Prediction via In-context Learning and Test-time Training. NeurIPS 2025 Workshop.
Paper
Guanghao Wei
Equal contribution
, Yining (Sam) Huang
Equal contribution
, Chenru Duan, Yue Song, Yuanqi Du (2024). Navigating Chemical Space with Latent Flows. NeurIPS 2024.
Paper
Zuobai Zhang
Equal contribution
, Pascal Notin
Equal contribution
, Yining (Sam) Huang, Aurelie Lozano, Vijil Chenthamarakshan, Debora Marks, Payel Das, Jian Tang (2024). Multi-Scale Representation Learning for Protein Fitness Prediction. NeurIPS 2024.
Paper
Yining (Sam) Huang
Equal contribution
, Zuobai Zhang
Equal contribution
, Jian Tang, Debora Marks, Pascal Notin (2024). Augmenting Evolutionary Models with Structure-Based Retrieval. ICML 2024 Workshop.
Paper
Dina Sharon
Equal contribution
, Yining (Sam) Huang
Equal contribution
, Motolani Oyewole, Sammy Mustafa (2024). How to Go with The Flow: An Analysis of Flow Matching Molecular Docking Performance with Priors of Varying Information Content. ICLR 2024 Workshop.
Paper
Yining (Sam) Huang
Equal contribution
, Steffanie Paul
Equal contribution
, Debora Marks (2023). An Energy Based Model for Incorporating Sequence Priors for Target-Specific Antibody Design. NeurIPS 2023 Workshop.
Paper
Yuanqi Du
Equal contribution
, Yingheng Wang
Equal contribution
, Yining (Sam) Huang, Jianan Canal Li, Yanqiao Zhu, Tian Xie, Chenru Duan, John Gregoire, Carla P Gomes (2023). M²Hub: Unlocking the Potential of Machine Learning for Materials Discovery. NeurIPS 2023.
Paper
Zaixi Zhang
Equal contribution
, Jiaxian Yan
Equal contribution
, Yining (Sam) Huang
Equal contribution
, Qi Liu, Enhong Chen, Mengdi Wang, Marinka Zitnik (2023). Geometric Deep Learning for Structure-Based Drug Design: A Survey. ACM Computing Survey.
Paper
Qiwen Zhang, Xueke Tian, Guang Chen, Ze Yu, Xiaojian Zhang, Jingli Lu, Jinyuan Zhang, Peile Wang, Xin Hao, Yining (Sam) Huang, Zeyuan Wang, Fei Gao, Jing Yang (2022). A Prediction Model for Tacrolimus Daily Dose in Kidney Transplant Recipients With Machine Learning and Deep Learning Techniques. Frontiers in Medicine.
Paper