Overview
Personal Profile
Disclaimer: Any opinions expressed on LinkedIn are the author’s own, made in the author's individual capacity, and do not necessarily reflect the views of NLR.
Evan Komp works to integrate deep learning for protein engineering, specifically for drives here at NLR related to plastic upcycling and novel C1 conversion systems, but aims to do so in a modular and generalizable way such that tools can be easily applied to new systems and built upon. Komp also has experience applying data science and machine learning to a myriad of other application spaces, and acts as a bridge between theoretical plus experimental expertise and machine learning. Additionally, he's interested in some novel tasks that yet have to be well established, such as solvent and pH tolerance/design.
Professional Experience
Lab Research Intern, Phibro Animal Health (2017)
Process Control Engineering Intern, WestRock Paper Company (2018–2019)
Chemical Machine Learning Intern, ArrePath Science (2022)
Education/Academic Qualification
Bachelor, Chemical Engineering, Oregon State University
PhD, Chemical Engineering Data Science, University of Washington
Master, Chemical Engineering Data Science, University of Washington
Fingerprint
- 1 Similar Profiles
Collaborations and Top Research Areas From the Past 5 Years
Research Output
- 3 Article
-
Building an Expanded Bio-Based Economy Through Synthetic Biology: Article No. 108775
Garza Elizondo, A., del Valle Kessra, I., Prates, E., Komp, E., Phillips, E., Ashok, N., Jacobson, D., Webb, E., Bomble, Y., Alexander, W., Tannous, J., Tsai, C.-J., Parrott, W., Yang, X., Urbanowicz, B., Bartley, L., Maranas, C., Tuskan, G., Guss, A. & Eckert, C., 2026, In: Biotechnology Advances. 87, 30 p.Research output: Contribution to journal › Article › peer-review
-
Cross-Kingdom Comparative Genomics Reveal the Metabolic Potential of Fungi for Lignin Turnover in Deadwood
Kijpornyongpan, T., Kuatsjah, E., Komp, E., Evans, J., Ruiz-Duenas, F. & Salvachua, D., 2025, In: Nature Ecology and Evolution. 9, p. 1599-1613 15 p.Research output: Contribution to journal › Article › peer-review
2 Scopus Citations -
Machine Learning-Guided Identification of PET Hydrolases from Natural Diversity
Norton-Baker, B., Komp, E., Gado, J., Denton, M., Mathews, I., Murphy, N., Erickson, E., Storment, O., Sarangi, R., Gauthier, N., McGeehan, J. & Beckham, G., 2025, In: ACS Catalysis. 15, 18, p. 16070-16083 14 p.Research output: Contribution to journal › Article › peer-review
2 Scopus Citations
Awards and Honors
-
Data Intensive Research Enabling Clean Technology Fellowship
Komp, E. (Recipient), 2022
Prize: Honorary award