Jingbo Liu

Professor Jingbo Liu is a distinguished academic with a robust background in statistics and electrical and computer engineering. Currently serving as an Assistant Professor at the University of Illinois Urbana-Champaign, Dr. Liu is renowned for their pioneering work in statistical machine learning, Bayesian modeling, and optimization methods. Their research is particularly impactful in diverse application areas such as healthcare, energy systems, transportation, and social networks, where they leverage advanced statistical techniques to address complex challenges. Dr. Liu's academic journey began at Tsinghua University, where they earned a Bachelor of Engineering in Electronic Engineering. This foundational education was further enriched by their pursuit of graduate studies at Princeton University, where they obtained both a Master of Arts and a Ph.D. in Electrical Engineering. During their doctoral studies, Dr. Liu developed a keen interest in signal processing, information theory, coding theory, and high-dimensional statistics, which continue to be central themes in their research endeavors. Throughout their career, Dr. Liu has been the recipient of numerous prestigious awards, underscoring their contributions to the field. Notably, they were honored with the Thomas Cover Dissertation Award in 2018, a testament to the groundbreaking nature of their doctoral research. Additionally, Dr. Liu has been recognized with the National Science Foundation CAREER Award, the Google Faculty Research Award, and the Sloan Research Fellowship, each highlighting their innovative approach and commitment to advancing knowledge in their areas of expertise. In their role at the University of Illinois Urbana-Champaign, Dr. Liu is dedicated to fostering an environment of academic excellence and innovation. They are actively involved in mentoring students and collaborating with colleagues to push the boundaries of what is possible in statistical inference and information-theoretic research. Dr. Liu's work not only contributes to the academic community but also has practical implications, influencing the development of more efficient and effective systems in various industries. Dr. Liu's research is characterized by a deep understanding of both theoretical and practical aspects of their field. By integrating concepts from high-dimensional statistics and information theory, they are able to develop novel solutions that address real-world problems. Their work in coding theory, for example, has implications for improving data transmission and storage, while their contributions to signal processing enhance the accuracy and reliability of communication systems. As a thought leader in their field, Dr. Liu continues to explore new frontiers in statistical machine learning and Bayesian modeling. Their commitment to interdisciplinary research and collaboration ensures that their work remains at the cutting edge of technology and innovation. Through their teaching and research, Dr. Liu is shaping the next generation of engineers and statisticians, equipping them with the skills and knowledge needed to tackle the challenges of tomorrow.