Tulay Adali

Dr. Tulay Adali is a Distinguished University Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC), where she directs the Machine Learning for Signal Processing Lab (MLSP-Lab). She holds a Ph.D. in Electrical Engineering from North Carolina State University (1992), with prior degrees including an M.S. from NCSU (1988) and a B.S. from Middle East Technical University, Turkey (1987).

Her research focuses on developing advanced machine learning methods for signal processing, particularly in multimodal data fusion, statistical signal analysis, and tensor factorizations. Primary applications include medical imaging (fMRI, sMRI, EEG) for neuropsychiatric disorders like schizophrenia, remote sensing, and misinformation detection. She pioneers flexible data-driven approaches that minimize traditional modeling assumptions.

Publication analysis reveals dominant themes in neuroimaging innovation, especially multimodal fusion techniques (ICA/IVA) for identifying biomarkers in brain disorders. Recent work emphasizes large-scale fMRI analysis, individualized brain network mapping, and schizophrenia diagnostics using joint tensor/matrix decomposition.

• IEEE Fellow & AIMBE Fellow
• Humboldt Research Award (2020)
• IEEE SPS Best Paper Award (2010, 2011)
• Fulbright Scholar
• USM Regents' Faculty Research Award

As lab director, she mentors PhD candidates including Vince Calhoun (now Professor at University of New Mexico) and Hualiang Li. Collaborates internationally with Peter Schreier (Paderborn University) on multi-modal data challenges. Leads major projects funded by NSF (CAREER Award) and Humboldt Foundation.

Holds editorial leadership roles including Editor-in-Chief of IEEE Signal Processing Magazine and VP for Technical Directions at IEEE Signal Processing Society. Organized flagship conferences like ICASSP and MLSP.