People

Paris
Smaragdis
Professor
Music Technology
Music
Paris Smaragdis is a Professor of Music Technology at MIT, holding a shared appointment between Music & Theater Arts Section and Electrical Engineering and Computer Science.  He obtained his B.Mus. (Cum Laude, ’95) from Berklee College of Music, and his S.M. (’97) and Ph.D. (’01) from the Massachusetts Institute of Technology, studying under Barry Vercoe.  He has been a Research Scientist at Mitsubishi Electric Research Labs, a Senior Research Scientist at Adobe Research, and an Amazon Scholar with Amazon’s AWS.  He spend 15 years as a professor at the University of Illinois Urbana Champaign in the Computer Science Department, where he spearheaded the design of the CS+Music program, and served as an Associate Director of the School of Computer and Data Science.
 
His research lies in the intersection of signal processing and machine learning, especially as it relates to sound and music.  He has contributed multiple widely used methods for source separation and audio analysis throughout his 150+ publications and 60+ US and international patents.  His work in audio generation and processing has been productized many times worldwide and has been widely used in personal computers, commercial systems, and music and film production.
 
He has been recognized by the MIT Technology Review as one of the “world’s top innovators under 35 years old” in 2006 (TR35 award) and he has received the IEEE Signal Processing Society (SPS) Best Paper Award twice (2017,2020) recently.  He was elected an IEEE Fellow (class of 2015), and selected as an IEEE SPS Distinguished Lecturer (2016-2017). Within IEEE SPS he has served as the chair the Machine Learning for Signal Processing Technical Committee, the Audio and Acoustic Signal Processing Technical Committee, and the Data Science Initiative.  He has been elected to and served in the IEEE Signal Processing Society Board of Governors, and recently served as the Editor in Chief of the ACM/IEEE Transactions on Audio, Speech, and Language Processing.  His work on post-processing historical recordings for the documentary “The Beatles: Get Back” resulted in an Emmy award for Sound Editing for a Nonfiction or Reality Program in 2022.
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