Location
2715
Phone
Primary Website
Biography
Dr. Raed Al Kontar is an assistant professor in the Industrial & Operations Engineering department. He is also an affiliate with both the Michigan Institutes for Data Science and Computational Discovery and Engineering. Dr. Al Kontar leads the “Data Science Lab,” which focuses on data science using probabilistic models, with an emphasis on precision/personalized data science where knowledge from diverse data sources is effectively integrated. Dr. Al Kontar’s research has been highly recognized, with his group winning 12 best paper awards since 2022 across the Institute for Operations Research and the Management Sciences (INFORMS), the American Statistical Association (ASA), and the Institute of Industrial and Systems Engineers (IISE). His research is currently supported by the National Science Foundation (NSF), including a 2022 CAREER award, the National Institutes of Health (NIH), the National Library of Medicine (NLM), and various industry collaborators.
Education
- PhD, University of Wisconsin-Madison, 2018, Industrial and Systems Engineering
- MS, University of Wisconsin Madison, 2017, Statistics
- BE, American University of Beirut, 2014, Civil and Environmental Engineering (Mathematics Minor)
Research Interests
Dr. Al Kontar works on developing data science methods for solving engineering problems. He also enjoys occasional theoretical endeavors beyond application. His focus is on personalized and distributed data analytics, where knowledge from diverse data sources is effectively integrated. This approach allows sources to retain personalized models tailored to their unique features, distribute or decentralize model inference, and protect personal data when needed.
Research Keywords: Data Science, Personalization, Collaboration, Heterogeneity, Federated Learning, Uncertainty Quantification, Black-box optimization, Digital Twins
Professional Service
- Institute of Industrial and Systems Engineers (IISE)
- Institute for Operations Research and the Management Sciences (INFORMS)
- American Statistical Association (ASA)
Awards
- 2024 IISE Transactions Service Award (2024)
- NSF CAREER Award (2022)
- Best Refereed Paper Recognition, Quality, Statistics & Reliability (QSR) section, INFORMS Annual Meeting (2023)
- Featured Article in the December 2023 Issue of the Industrial and Systems Engineering (ISE) Magazine (2023)
- Best Paper Recognition, Data Mining (DM) section, INFORMS Annual Meeting (2023)
- Best Paper Recognition, Physical and Engineering Sciences, Joint Statistical Meetings (JSM) (2023)
- Best Paper Recognition, Data Mining (DM) section, INFORMS Annual Meeting (2022)
- Best Refereed Paper Recognition, Quality, Statistics & Reliability (QSR) section, INFORMS Annual Meeting (2022)
- Best Track Paper Recognition, Data Analytics and Information Systems (DAIS) division, IISE Annual Conference
- American University of Beirut Valedictorian and Commencement Speaker (2014)
Publications
- “Multi-agent Collaborative Bayesian Optimization via Constrained Gaussian Processes.” Qiyuan Chen, Raed Kontar. Technometrics, 2024.
- “Personalized PCA: Decoupling Shared and Unique Features.” Naichen Shi, Raed Kontar. Journal of Machine Learning Research (JMLR), 2024.
- “Personalized Feature Extraction for Manufacturing Process Signature Characterization and Anomaly Detection.” Naichen Shi, Shenghan Guo, Raed Kontar. Journal of Manufacturing Systems, 2024.
- “Personalized Dictionary Learning for Heterogeneous Datasets.” Geyu Liang, Naichen Shi, Raed Kontar, Salar Fattahi. Conference on Neural Information Processing Systems (NeurIPS), 2024.
- “Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity Modeling.” Xubo Yue, Raed Kontar. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
- “Federated Multi-output Gaussian Processes.” Seokhyun Chung, Raed Kontar. Technometrics, 2024.
- “Federated Data Analytics: A Study on Linear Models.” Xubo Yue, Raed Kontar, Ana Maria Estrada Gomez. IISE Transactions, 2024.
- “Personalized Federated Learning via Domain Adaptation with an Application to Distributed 3D Printing.” Naichen Shi, Raed Kontar. Technometrics, 2023.
- “GIFAIR-FL: An Approach for Group and Individual Fairness in Federated Learning.” Xubo Yue, Maher Nouiehed, Raed Kontar. INFORMS Journal on Data Science (IJDS), 2022.
- “Gaussian Process Parameter Estimation Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits.” Hao Chen, Lili Zheng, Raed Kontar, Garvesh Raskutti. Journal of Machine Learning Research (JMLR), 2022.