Two Department Professors Receive NSF CAREER Awards
Two Department of Statistics and Data Science Professors Receive NSF CAREER Awards in 2026
Professor Feng Ruan was recently recognized by the National Science Foundation with a CAREER award effective June 1st, 2026. Professor Ruan’s recognition is for his work titled “Beyond Multi-Index Models: Statistical and Algorithmic Foundations for Feature Learning in Compositional Architectures”. This project will work to bridge the gap between interpretable statistical methods and modern high-performing predictive systems by developing compositional learning models that combine rigorous statistical foundations with the ability to reliably uncover predictive structure in complex data. To achieve these goals, Professor Ruan will develop a unified framework for learning compositional models and understanding when such models discover true low-dimensional structure in data.
Additionally, Professor Kaize Ding was recognized by the National Science Foundation with a CAREER Award effective October 1st, 2026. Professor Ding was given the award for his work titled “OPENALIGN: Towards Open-World Preference Alignment for Large Language Models”. This project will seek to advance the foundations of reliable and efficient LLM systems that can understand, adapt to, and align with diverse human preferences in open-world environments. Professor Ding’s research will also contribute to scientific discovery, education and workforce development through the integration of research and training activities.
The CAREER award is described by the National Science Foundation as “one of the Foundation's most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education.” The Department of Statistics and Data Science extends their congratulations to Professor Ding and Professor Ruan for their achievement.