This talk will discuss how data science is accelerating innovation in STEM fields. These tools enable the efficient handling of valuable data, the identification of patterns in large data collections, the development of predictive models, and the optimal design of experiments. I will show examples from the field of materials science where tools can speed up the discovery and optimization of new materials and reduced the associated cost. The fast adoption of data science in STEM applications calls for an equally fast incorporation of these material in undergraduate and graduate education.In the second part of the talk, I will introduce data science and cloud computing resources in nanoHUB, an open cyberinfrastructure for cloud scientific computing that seeks to maximize the impact of simulations and data in education and research. A hands-on tutorial will introduce participants to modern tools to manage, organize, and visualize data as well as machine learning techniques to model data and make decisions. We will discuss learning modules designed to introduce students and researchers to the fundamentals as well as resources for advanced practitioners.

Alejandro Strachanis a Professor of Materials Engineering at Purdue University, Director, DoD ONR MURI “Predictive Chemistry and Physics at Extreme Conditions”, PCP@Xtreme, and the Deputy Director of NSF’s nanoHUB. Before joining Purdue, he was a Staff Member in the Theoretical Division of Los Alamos National Laboratory and worked as a Postdoctoral Scholar and Scientist at Caltech. He received a Ph.D. in Physics from the University of Buenos Aires, Argentina. Prof. Strachan’s research focuses on the development of predictive atomistic and multiscalemodels to describe materials from first principles and their combination with data scienceto address problems of technological or scientific importance. Areas of interest include: high-energy density and active materials, metallic alloys for high-temperature applications, materials and devices for nanoelectronics and energy, as well aspolymers and their composites. In addition, Strachan’s scholarly work includes cyberinfrastructure to maximize the impact of and democratize access to models and data for research and education. Prof. Strachan has published over 180 peer-reviewed scientific papers and his contributions to research and education have beenrecognized byseveral awards, including the Early Career Faculty Fellow Award from TMS in 2009, his induction as a Purdue University’s Faculty Scholar (2012-2017), and the R&D 100 award in the area of software and services for nanoHUB.

University of Puerto Rico

Researchers should cite this work as follows:

• Alejandro Strachan (2022), "Learning and Teaching Data Science using nanoHUB’s Cloud Resources," https://nanohub.org/resources/35958.

  BibTex | EndNote

1. data science
2. design of experiments
3. e-science
4. materials science
5. predictive models
6. teaching and learning