Zhimei Ren

Professor Zhimei Ren is an esteemed Assistant Professor of Statistics and Data Science at the Wharton School, University of Pennsylvania. With a robust academic background, she earned her Ph.D. in Statistics from Stanford University in 2021, following her B.S. in Statistics from Peking University in 2016. Her academic journey is marked by a commitment to advancing statistical methodologies and their applications in various domains. Before her current role at Wharton, Professor Ren honed her research skills as a Postdoctoral Researcher at the University of Chicago from 2021 to 2023. During her postdoctoral tenure, she engaged in cutting-edge research that contributed significantly to the field of statistics and data science. Her work is characterized by a focus on practical applications and theoretical advancements, bridging the gap between complex statistical theories and real-world problems. Professor Ren's research interests are diverse and impactful, encompassing distribution-free inference, multiple hypothesis testing, data-driven decision making, causal inference, and survival analysis. Her work in distribution-free inference aims to develop statistical methods that do not rely on specific data distribution assumptions, enhancing the robustness and applicability of statistical conclusions. In the realm of multiple hypothesis testing, she seeks to improve the accuracy and efficiency of statistical tests when dealing with numerous hypotheses simultaneously. In addition to her research, Professor Ren is dedicated to teaching and mentoring the next generation of statisticians and data scientists. She is known for her engaging teaching style and her ability to convey complex statistical concepts in an accessible manner. Her courses often integrate theoretical knowledge with practical applications, preparing students to tackle real-world challenges with confidence and expertise. Professor Ren's contributions to the field have been recognized through various awards and publications in prestigious journals. Her work continues to influence the development of statistical methodologies and their application across different sectors. As a thought leader in her field, she frequently collaborates with researchers and practitioners to address pressing issues in statistics and data science. Outside of her professional endeavors, Professor Ren enjoys exploring new technologies and their potential to transform data analysis. She is also an advocate for diversity and inclusion in the field of statistics, actively working to create opportunities for underrepresented groups in academia and beyond. Her commitment to excellence and innovation makes her a valuable asset to the academic community and a respected figure in the world of statistics and data science.