adali_awardMore than twenty years ago, Tulay Adali stepped onto UMBC’s campus as an assistant professor right after receiving her PhD. Much has changed since then.

Now a professor of Computer Science and Electrical Engineering, Dr. Adali runs a highly active Machine Learning for Signal Processing Lab (MLSP­Lab). Her recent appointment as an IEEE Signal Processing Society Distinguished Lecturer has prompted invitations to speak around the world about her research in the theory and development of algorithms for signal processing. This March, Dr. Adali was awarded the University System of Maryland Regents’ Faculty Award for Scholarship, Research, or Creative Activity.

Her secret to success?

“Planning or thinking about the future is not something I do,” said Dr. Adali in her acceptance speech at the Presidential Faculty and Staff Ceremony where she was honored in March. “I rather make sure I enjoy what I do and have fun along the way.” Her technique seems to be paying off. For proof, just take a look at the recognition received by her research in two distinct areas: the development of powerful data­driven methods, and the analysis and fusion of medical imaging data. In 2008, Dr. Adali was elected a fellow of the American Institute for Medical and Biological Engineering (AIMBE). In 2009, the Institute of Electrical and Electronics Engineering (IEEE) elected her a fellow for her work on the theory and practice of statistical signal processing.

In 2011, a paper by Dr. Adali and colleagues titled “Complex ICA using nonlinear functions” received the 2010 IEEE Signal Processing Society Best Paper Award. The work develops a complete framework, allowing for the processing of complex data in a manner similar to the real­valued case, eliminating the need to make many of the simplifying assumptions commonly employed. The results of this NSF­funded study led to the development of a complete data­driven framework that enables joint use of sample dependence and higher­order­statistics.

Dr. Adali’s work in medical image analysis and fusion has also gained notoriety. She has been working on methods for data­driven analysis of medical imaging data, and for the analysis of functional magnetic resonance imaging (fMRI) data for understanding brain function. She and her colleagues discovered that fusing more than two modalities increases the sensitivity and specificity of the analyses of fMRI, electroencephalography (EEG) and structural MRI data. In March 2011, an IEEE Spectrum article mentioned her success in obtaining very high classification accuracy in identifying mental disorders in patients. Then in April 2011, in addition to her ongoing projects funded by the NSF, NIH, and the Mind Research Network, she received a grant from Michelin Research to study irregular wear detection in tires, where the new data-driven framework is applied to a completely new problem domain.

These notable research advances made Dr. Adali stand out as a nominee for this year’s Regents’ Faculty Award for Scholarship, Research, or Creative Activity. It is the highest honor given by the Board of Regents to faculty members, given to faculty members who have gone above and beyond the call of duty. This year, Dr. Adali joins only three other USM faculty members who were recognized for their exceptional research contributions. “Dr. Adali has been steadily building her research career and I am not surprised by the award since her research is remarkable,” says Dr. Carter, CSEE Department Chair. “I see her continuing to grow her research in areas of signal processing for medical applications and becoming a key UMBC faculty member