Prof. Paris Smaragdis

Professor Smaragdis's primary research interests revolve around making machines that can listen. He has done plenty of work on signal processing, machine learning and statistics as they relate to artificial perception, and in particular computational audition and music processing. He also loves working on anything related to audio. The bulk of his work on audio is on source separation, and various novel machine learning approaches for traditional signal processing problems. At MIT Smaragdis is part of the Music Technology program, a member of the RLE, and an AI+D faculty member of Electrical Engineering & Computer Science (EECS).

Smaragdis completed his masters, Ph.D. and a postdoc at the Machine Listening Group at the MIT Media Lab under the supervision of Barry Vercoe. He was previously a professor and associate director of the School of Computer and Data Science at UIUC where he created the CS+Music program. Smaragdis also worked at AWS as an Amazon Scholar, he started Adobe Research's audio research, he was a research scientist at MERL, and have spent some time at Interval Research and Starlab. Smaragdis was also a visiting scientist at MIT’s McGovern Institute for Brain Research. In 2006 he was selected by MIT’s Technology Review as one of the year’s top young technology innovators.

Professor Smaragdis is an IEEE fellow, was an IEEE Distinguished Lecturer for 2016-2017, and he has been the Editor-in-Chief for the ACM/IEEE Transactions on Audio, Speech, and Language Processing. He has previously chaired the IEEE SPS Audio and Acoustic Signal Processing Technical Committee, the IEEE SPS Machine Learning for Signal Processing Technical Committee, the IEEE SPS Data Science Initiative, and he has served in the IEEE SPS Board of Governors.

Smaragdis is a descendant of a long music academic lineage dating to the early 1600s.