معرفی
Su Chen is an Associate Professor of Instruction in the Department of Statistics and Data Science at the University of Texas at Austin. She previously served as an Assistant Teaching Professor at Rice University's D2K Lab and directed their Data Science Minor Program. Her roles include curriculum design, pedagogical innovation, and experiential learning in statistics and data science. She also holds a Master's in Actuarial Science and worked in the insurance sector before transitioning to academia. Currently, she oversees the SDS Experiential Learning program at UT-Austin.
Education:
- Ph.D. in Statistics, University of Texas at Austin (2020)
- Master of Science in Math and Actuarial Science, University of Texas at Austin
- Bachelor of Science in Applied Mathematics, Zhejiang University (China)
Research Interests: Su Chen specializes in experiential learning methodologies within data science education. Her work emphasizes curriculum development and innovative teaching strategies. She also maintains expertise in Bayesian statistics and their applications to high-dimensional data analysis. Her teaching philosophy prioritizes student autonomy, collaborative learning environments, and emotional engagement in education.
Articles: Her research spans geochemical processes in Earth's mantle and magmatic systems, with recent publications exploring trace element partitioning, redox equilibria in melts, and volatile transport dynamics. These studies address topics like kimberlite petrogenesis, mantle dynamics, and planetary evolution, reflecting interdisciplinary strengths in both geosciences and statistical methods.
Scientific Awards:
- Mineralogical Society of America Award (2021)
Teaching and Advising: Su Chen has developed undergraduate and graduate courses at UT-Austin (SDS 357), Rice University (DSCI 101, COMP 680), and Texas A&M. She mentors capstone projects addressing real-world challenges such as transportation optimization, emergency response fleet analysis, and environmental sustainability. Her pedagogical contributions include Python-based simulation curricula and collaboration with platforms like Software Carpentry.
Labs and Teams: As Director of SDS Experiential Learning, she leads initiatives integrating practical data science training with academic coursework. Her work involves designing interdisciplinary learning experiences and fostering connections between academic research and industrial applications.
