The upcoming Data Science Community Research Talks will feature two researchers using data science approaches in their research, one studying ethical ways to conduct human science while maintaining data privacy, and another using techniques to accelerate the development of two-dimensional materials.
Timothy Brick, assistant professor of human development and family studies and faculty co-hire of the Institute for Computational and Data Sciences (ICDS), and Wesley Reinhart, assistant professor of materials science and engineering and ICDS faculty co-hire, will present the online talks, scheduled from 11 a.m. to noon on Thursday, April 1. Advance registration is required.
Brick will discuss an ethical concern related to data collection for human-focused research. Researchers who use personal or private data to inform their research are also responsible for ensuring that their research methods are transparent, and their work is reproducible. When personal data is involved, it creates a dilemma because those data cannot be shared. Furthermore, study participants aren’t always reimbursed for their role in creating data for studies. Brick will discuss a research paradigm, Maintained Individual Data Distributed Likelihood Estimation (MIDDLE), that he and collaborators designed to maintain data privacy while enabling research in the behavioral, social and health sciences.
Reinhart will discuss ways that data science techniques can be used to accelerate the materials design process. Reinhart, who collaborates with the National Science Foundation-funded 2D Crystal Consortium – Materials Innovation Platform, will share the complexities of designing materials that have specific properties, structure and processing steps. He will also discuss his exploration of techniques to remove steps that, in the past, relied on human intuition.
The Data Science Community is a grassroots initiative supported by Penn State's Teaching and Learning with Technology, Institute for Computational and Data Sciences and University Libraries. To learn more about Data Science Community events or to join the community mailing list, visit datascience.psu.edu.