He received the Ph.D. degree in electrical and computer engineering from the University of Illinois at Urbana-Champaign. Dr. Fu’s research interests are interdisciplinary research in Machine Learning, Computational Intelligence, Data Mining, and Computer Vision. In particular, he creates machine learning algorithms to deal with data under uncertainties, such as high dimensionality, noise, multiple view, multiple modality, outliers, missing data, etc. He received seven Prestigious Young Investigator Awards from NAE, ONR, ARO, IEEE, INNS, UIUC, Grainger Foundation; and seven Best Paper Awards from IEEE, IAPR, SPIE, SIAM. Proposed Title: Multimodal and Multimodality Data Analytics under Uncertainty