Professor Soltanalian Receives Signal Processing Society (SPS) Young Author Best Paper Award

Professor  Soltanalian is set to receive the 2017 IEEE Signal Processing Society Young Author Award. The prestigious award will be presented to Dr. Soltanalian by IEEE Signal Processing Society President, Professor Ali H. Sayed, in April during the opening ceremony of the 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) in Calgary, Canada.

Dr. Soltanalian was named the winner for the paper Designing Unimodular Codes Via Quadratic Optimization, which was co-authored by Petre Stoica and published in IEEE Transactions on Signal Processing, Volume 62, No. 5, March 2014. Eligibility for the award is based on a three-year window, afforded to assess the impact of papers through a longer time frame. All eligible papers then go through a careful selection process administered by the society and will be judged on the basis of general quality, originality, subject matter, and timeliness. This paper deals with quadratic programming which refers to a procedure used in solving commonly encountered problems of mathematical optimization for a certain class of functions.

“In the paper, we introduce efficient ‘power method-like iterations’ for computationally efficient quadratic programming that can handle various practical signal constraints and likely open new avenues in signal processing in large-scale scenarios (e.g. for big data and massive MIMO applications),” said Soltanalian. “A more fundamentally transformative contribution of the paper lies in the fact that it develops an optimization framework capable of producing a posteriori optimality guarantees that are data-dependent. The data (or problem instance) dependent nature of a posteriori guarantees lays the ground for improved guarantees that can be offered as trust certificates along with the obtained approximate solutions. As a result, the emergence of such guarantees can be game-changing as it paves the way for a new set of applications, including e.g., machines that can evaluate how much they can trust their inference depending on the situation/environment, or confident decision-making in operations that are accuracy-sensitive.”

Dr. Soltanalian’s work was strongly endorsed by his peers, which included a professor from the University of Florida. “Dr. Soltanalian has created methods for generating optimality guarantees that are data-driven, enhanced, and are suitable for application in the kind of NP-hard optimization problems that are so common in signal processing, and present a real challenge in signal design,” the professor said. “His approach represents a truly novel development for the field. These exceptional contributions were a key consideration when I extended an invitation to Dr. Soltanalian to give a tutorial on the subject at ICASSP 2016.”

The award honors the author of an especially meritorious paper dealing with a subject related to the society’s technical scope and appearing in one of the society’s solely owned transactions or the Journal of Selected Topics in Signal Processing and who, upon the date of submission of the paper, is less than 30 years of age.

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