معرفی
Raed Al Kontar serves as an Associate Professor with tenure in the Industrial & Operations Engineering (IOE) department at the University of Michigan's College of Engineering. He leads the Data Science Lab and holds affiliate appointments with the Michigan Institute for Data Science and Computational Discovery and Engineering. His research bridges probabilistic modeling with engineering applications, focusing on personalized, collaborative, and distributed data analytics where knowledge from diverse sources is integrated while preserving privacy.
His research program addresses three core questions across descriptive, predictive, and prescriptive analytics: extracting shared/unique patterns across datasets, enabling collaborative model improvement while maintaining data privacy, and optimizing distributed trial-and-error processes. Key research areas include Federated Learning, Uncertainty Quantification, Bayesian Optimization, and Digital Twins, with applications spanning healthcare, manufacturing, and materials science. Current funding includes NSF (including a 2022 CAREER award), NIH, NLM, and industry partnerships.
- Research Trends: His recent publications demonstrate a strong focus on heterogeneous data integration through novel matrix/tensor factorization techniques, personalized PCA frameworks, and consensus-based distributed optimization. The work consistently bridges theoretical guarantees (e.g., identifiability conditions) with practical applications in hydrogel development, 3D printing, and pharmaceutical safety.
- Award Highlights: His group has won 12 best paper awards since 2022 across INFORMS, ASA, and IISE, including the 2024 Wilson Prize and INFORMS Data Mining Section's Best General Track Paper.
Dr. Al Kontar has successfully placed multiple PhD students in tenure-track positions including Naichen Shi (Northwestern), Xubo Yue (Northeastern), and Seokhyun Chung (University of Virginia). His lab maintains active collaborations with medical researchers (NIH/NLM projects), materials scientists (autonomous experimentation), and pharmaceutical safety experts. The lab combines theoretical innovation with real-world impact, exemplified by their NSF CAREER-funded work on the Internet of Federated Things.
