Data Chemist Network
Data Chemist Network (DCN) vision
Fundamentally change the academic and funding landscapes by building a network that recognizes excellence amongst faculty members whose identities and/or institutions have been historically underrepresented in NSF centers, enabling and amplifying their value and contributions to the frontiers of science.
Data Chemist Network (DCN) mission
The mission of the DCN is to provide a network for access and collaboration for faculty from underrepresented racial groups who are at institutions that are not traditionally involved in multi-institutional centers. What makes the DCN unique is the recognition that value and expertise can come from faculty of different backgrounds and from all institutional levels. As such, the DCN will consist of both Assistant and Associate Professors, from a range of institutions, such as liberal arts, predominantly undergraduate, R1, R2, HBCU, HSI, and tribal colleges. As part of C-CAS, the DCN shares the research goals of using machine learning, data science, and synthetic chemistry to develop new tools to understand, analyze, and predict chemical transformations.
We accomplish our mission by focusing on the following areas:
- Amplification [of voices] - Highlighting faculty expertise and perspective to an expanded audience, which yields stronger professional networks
- Community - Building a “community of practice” that fosters collective growth in the field of data science, as well as methods of understanding, measuring, and predicting chemical reactivity
- Collaboration - Combined resources and joint projects result in accelerated science, publications, and large-scale grant/center proposals
- Mentorship - Multidimensional mentorship where each member of the community has the agency to contribute and benefit (e.g., peer mentoring, mentorship across career stages, etc.)