Wennie Wang
Assistant Professor, McKetta Department Of Chemical Engineering at The University of Texas at Austin
Austin, Texas, United States
Summary
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Senior🎓
Top SchoolWennie Wang is an assistant professor in chemical engineering at UT Austin who builds predictive, first-principles models to tailor optical, electronic, and transport properties of materials for energy sustainability. With a PhD in computational materials science from UCSB and postdoctoral work at the University of Chicago, she specializes in understanding and exploiting defects in optoelectronic materials and interfaces. Her research blends rigorous electronic-structure calculations with applied device-relevant questions, driving discovery of novel materials platforms for energy technologies. Beyond the lab, she is committed to inclusive STEM education and public-policy engagement, developing outreach and career-development resources for early-career scientists. An experimental collaborator at heart, she brings interdisciplinary experience from internships in photovoltaics and aerospace composites to inform computational predictions.
8 years of coding experience
10 years of employment as a software developer
Bachelor's of Science, Materials Science and Engineering, Bachelor's of Science, Materials Science and Engineering at Massachusetts Institute of TechnologyPhD, Materials Science- Computational Materials Science, PhD, Materials Science- Computational Materials Science at University of California, Santa Barbara
German, ChineseProgramming languages (1)
Github contributions (5)
wwwennie/spectra_fit
May 2019 - Dec 2019
Contributions:5 commits, 2 pushes, 1 branch in 6 months
wwwennie/pycdft
May 2020 - May 2022
Contributions:4 PRs, 2 pushes in 2 years
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