Welcome to my page!
My name is Chasz Griego (he/him). I have a PhD in Chemical Engineering, and I am a Science and Engineering Librarian at Carnegie Mellon University. (CMU)
You can learn more about my research and my interests on this site.
Contact Me
cgriego@andrew.cmu.edu
Office 4410, Sorrells Library
4th Floor, Wean Hall, Carnegie Mellon University
Pittsburgh, PA 15213
More About Me
As a Science and Engineering Librarian, I serve as the liaison to the departments of Chemistry, Chemical Engineering, and Materials Science and Engineering at CMU. I first started at the CMU Libraries in June 2022 as an Open Science Postdoctoral Associate, helping the Open Science and Data Collaborations Program improve outreach, teaching, research, and overall program development. I received a B.S. in Chemical Engineering from the New Mexico Institute of Mining and Technology, then a PhD from the University of Pittsburgh. For my dissertation, I studied computational models that facilitate screening catalyst materials with quantum chemistry simulations. My professional interests include studying reproducibility in computational research, teaching Python programming for data science, and advocating open science and scientific skepticism. My personal interests include playing guitar, board games, and listening to comedy podcasts.
Research
Measuring Reproducibility with Open Science Tools
Teaching
- Enhancing Reproducibility and Collaboration with Open Research Tools. 2023. OSF Page
- Current workshops listed here.
Research Tools and Personal Knowledge Management
Below is an example of how I use tools and resources to manage the flow of research, discovery, and scholarly output.
*Obsidian logo is outdated
Professional Information
Curriculum Vitae
Publications of Note
CMU Libraries
- Op-ed on Collaborative and Reproducible Notebooks. 2022
- Griego CD, Beltran L, Herckis L. Open Science Recommendation Systems for Academic Libraries. Journal eScience Librarianship. 2024 (Accepted).
- Bongiovanni E, Gainey M, Beltran L, Griego CD. The Open Science Book. Association of College & Research Libraries. 2024 (Editor, In progress)
University of Pittsburgh
- Dissertation, Rethinking Computational Catalyst Searches with Alchemical Perturbation Density Functional Theory, 2022.
- Created Figure 1 in Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems. Chemical Reviews. 2021 10.1021/acs.chemrev.1c00107
- Griego CD, Kitchin JR, Keith JA. Acceleration of catalyst discovery with easy, fast, and reproducible computational alchemy. Int J Quantum Chem. 2020; 10.1002/qua.26380
- Griego CD, Zhao L, Saravanan K, Keith JA. Machine learning corrected alchemical perturbation density functional theory for catalysis applications. AIChE J. 2020; 10.1002/aic.17041
- Griego CD, Saravanan K, and Keith JA. Benchmarking Computational Alchemy for Carbide, Nitride, and Oxide Catalysts. Adv. Theory Simul. 2018; 10.1002/adts.201800142
