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Cagdas Bilen is a highly experienced researcher in the fields of signal processing, machine learning, and multimedia technology. Currently serving as Head of Research and previously as Staff Research Engineer at Audio Analytic since July 2018, Cagdas has held significant positions at various prestigious institutions, including Université de Strasbourg and Technicolor R&I. Cagdas's research contributions include work on source separation through nonnegative matrix/tensor factorization, blind calibration in sparse inverse problems, and enhancing MR image acquisition techniques. Academic qualifications include a PhD from the Polytechnic Institute of New York University, along with master's and bachelor’s degrees from Middle East Technical University. Cagdas has also contributed to multimedia education and has experience in developing innovative solutions for real-time video streaming and stereoscopic video technologies.