Posters

1. Kevin P. Greenman, Ava P. Amini, and Kevin K. Yang, “Benchmarking Uncertainty Quantification for Protein Engineering”. American Chemical Society Fall Meeting. San Francisco, CA, August 2023. (Accepted).
2. 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. May 2023.
3. 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. (Poster)
4. Charles McGill, Kevin Greenman, David Graff, Oscar Wu, and William H. Green. “Chemprop v1.5.0 New Features and Updates”. Machine Learning for Pharmaceutical Discovery and Synthesis Consortium Meeting. Cambridge, MA. April 2022.
5. Kevin P. Greenman, William H. Green, and Rafael Gómez-Bombarelli. “Artificial Intelligence Applications in the Design of Novel Dye Molecules with Targeted Optical Properties”. Society of Catholic Scientists Conference. Washington, DC, June 2021. (Poster)
6. Kevin Greenman, Logan Williams, and Emmanouil Kioupakis. “Lattice-Constant and Band-Gap Tuning in BInGaN Alloys for Higher-Efficiency LEDs”. University of Michigan Engineering Design Expo. Ann Arbor, MI, April 2019. (Poster)
7. Kevin Greenman and Peilin Liao. “Computational Catalysis with Density Functional Theory”. American Institute of Chemical Engineers Undergraduate Student Poster Competition. Pittsburgh, PA, October 2018. (Poster)
8. Kevin Greenman and Peilin Liao. “Computational Catalysis with Density Functional Theory”. Network for Computational Nanotechnology Undergraduate Research Experience Poster Session. West Lafayette, IN, July 2018. (Poster)