Posters
David E. Graff, Kevin P. Greenman, Hao-Wei Pang, Nathan Morgan, Jackson Burns, Angiras Menon, Shih-Cheng Li, Haoyang Wu, Jonathan Zheng, Anna Doner, Xiaorui Dong, Joel Manu, Kevin Spiekermann, William H. Green. “Chemprop v2.0.0: Stable Release and Future Plans.” Machine Learning for Pharmaceutical Discovery and Synthesis Consortium Meeting, Cambridge, MA, USA (April 2024).
Kevin P. Greenman, Temujin Orkhon, William H. Green, Rafael Gómez-Bombarelli. “Multi-Fidelity Deep Learning for Data-Efficient Molecular Property Models from Experimental and Computational Data.” AIChE Annual Meeting, Orlando, FL, USA (November 2023). PDF
Kevin P. Greenman. “Multi-Fidelity Computer-Aided Molecular Design.” AIChE Annual Meeting, Orlando, FL, USA (November 2023). PDF
Kevin P. Greenman, Temujin Orkhon, William H. Green, Rafael Gómez-Bombarelli. “Multi-Fidelity Deep Learning for Data-Efficient Molecular Property Models from Experimental and Computational Data.” Machine Learning for Pharmaceutical Discovery and Synthesis Consortium Meeting, Cambridge, MA, USA (October 2023).
David Graff, Kevin P. Greenman, Nathan Morgan, Oscar Wu, Angiras Menon, Hao-Wei Pang, Xiaorui Dong, Jackson Burns, Kevin Spiekermann, William H. Green. “Chemprop New Features and Updates.” Machine Learning for Pharmaceutical Discovery and Synthesis Consortium Meeting, Cambridge, MA, USA (October 2023).
Kevin P. Greenman, Ava P. Amini, Kevin K. Yang. “Benchmarking Uncertainty Quantification for Protein Engineering.” ACS Fall Meeting, San Francisco, CA, USA (August 2023). PDF
David Graff, Kevin P. Greenman, Oscar Wu, Shih-Cheng Li, and William H. Green. “Chemprop New Upcoming Features and Updates”. Machine Learning for Pharmaceutical Discovery and Synthesis Consortium Meeting, Cambridge, MA, USA (May 2023).
Kevin P. Greenman, Ava P. Soleimany, and Kevin K. Yang. “Benchmarking Uncertainty Quantification for Protein Engineering”. International Conference on Learning Representations – Machine Learning for Drug Discovery Workshop, Virtual (April 2022). PDF
David Graff, Kevin P. Greenman, Oscar Wu, Shih-Cheng Li, William H. Green. “Chemprop v1.5.0 New Features and Updates.” Machine Learning for Pharmaceutical Discovery and Synthesis Consortium Meeting, Cambridge, MA, USA (April 2022).
Kevin P. Greenman, William H. Green, Rafael Gómez-Bombarelli. “Artificial Intelligence Applications in the Design of Novel Dye Molecules with Targeted Optical Properties.” Society of Catholic Scientists Conference, Washington, DC, USA (June 2021). PDF
Kevin Greenman, Logan Williams, Emmanouil Kioupakis. “Lattice-Constant and Band-Gap Tuning in BInGaN Alloys for Higher-Efficiency LEDs.” University of Michigan Engineering Design Expo, Ann Arbor, MI, USA (April 2019). PDF
Kevin Greenman, Peilin Liao. “Computational Catalysis with Density Functional Theory.” AIChE Undergraduate Student Poster Competition, Pittsburgh, PA, USA (October 2018). PDF
Kevin Greenman, Peilin Liao. “Computational Catalysis with Density Functional Theory.” Network for Computational Nanotechnology Undergraduate Research Experience Poster Session, West Lafayette, IN, USA (July 2018). PDF