About Me

Experienced researcher and engineer working at the MN-AM as a Software Engineer. Prior to this role, I was working for the Center for Computational Toxicology and Exposure at the Environmental Protectional Agency as a subcontractor where I developed and applied machine learning models to predict a chemical's properties based on their structure and other physical characteristics. I completed my MSc in Chemical Engineering at Carnegie Mellon University where I was advised by Zachary Ulissi and worked on the development of and application an active learning framework for machine learning potentials to reduce computational time required for atomic simulations. This type of work helps us to further optimize and accelerate our ability to identify optimal catalysts for various applications as alternative fuel generation. I am always looking for new opportunities to leverage my skills and experience in data science and software engineering to address everyday problems using data-driven decision making.

1. https://pubs.acs.org/doi/10.1021/acs.chemrestox.4c00367
   Grace Patlewicz, Antony J. Williams, Matthew Adams, Imran Shah, and Katie Paul-Friedman. A cheminformatics workflow to select representative tsca chemicals for new approach methodology (nam) screening. Chemical Research in Toxicology, 38(1):129–144, 2025. PMID: 39655894.
2. https://www.sciencedirect.com/science/article/pii/S2468111322000445
   Matthew Adams, Hannah Hidle, Daniel Chang, Ann M. Richard, Antony J. Williams, Imran Shah, and Grace Patlewicz. Development of a csrml version of the analog identification methodology (aim) fragments and their evaluation within the generalised read-across (genra) approach. Computational Toxicology, 25:100256, 2023
3. https://pubs.acs.org/doi/10.1021/acs.chemrestox.2c00403
   Ann M. Richard, Ryan Lougee, Matthew Adams, Hannah Hidle, Chihae Yang, James Rathman, Tomasz Magdziarz, Bruno Bienfait, Antony J. Williams, and Grace Patlewicz. A new csrml structure-based fingerprint method for profiling and categorizing per- and polyfluoroalkyl substances (pfas). Chemical Research in Toxicology, 36(3):508–534, 2023
4. https://joss.theoj.org/papers/10.21105/joss.05035
   Muhammed Shuaibi, Yuge Hu, Xiangyun Lei, Benjamin M. Comer, Matt Adams, Jacob Paras, Rui Qi Chen, Eric Musa, Joseph Musielewicz, Andrew A. Peterson, Andrew J. Medford, and Zachary Ulissi. Amptorch: A python package for scalable fingerprint-based neural network training on multi-element systems with integrated uncertainty quantification. Journal of Open Source Software, 8(87):5035, 2023

• mattaadams1@gmail.com
• Knoxville, TN