Paris Smaragdis

Electrical and Computer Engineering
Paris Smaragdis
Associate Professor
  • Electrical and Computer Engineering
3231 Siebel Center for Comp Sci
201 N. Goodwin Ave.
Urbana Illinois 61801

Primary Research Area

  • Biomedical Imaging, Bioengineering, and Acoustics - Acoustics

For more information

Profile

Education

  • Ph.D. Massachusetts Institute of Technology, 2001, Advisor: Barry Vercoe

Biography

Paris Smaragdis is faculty at the Computer Science and the Electrical and Computer Engineering departments of the University of Illinois at Urbana-Champaign, as well as a senior research scientist at Adobe Research. He completed his masters, PhD, and postdoctoral studies at MIT, performing research on computational audition. His research is focused on machine learning approaches to solving various audio signal processing problems. In 2006 he was selected by MIT’s Technology Review as one of the year’s top young technology innovators for his work on machine listening, and in 2015 he was elevated to an IEEE Fellow for contributions in audio source separation and audio processing. He is currently an IEEE SPS Distinguished Lecturer.

He has been the chair of the ICA/LCA steering committee, the chair of the IEEE Machine Learning for Signal Processing Technical Committee, a member of the IEEE Audio and Acoustic Signal Processing Technical Committee, an Associate Editor for the IEEE Signal Processing Letters, and a Senior Area Editor for the IEEE Signal Processing Transactions. He holds 29 US patents and many other internationally.

Resident Instruction

  • ECE 310 - Digital Signal Processing
  • CS 361 - Probability and Statistics for Computer Scientists
  • ECE 403 - Audio Engineering
  • CS 598 - Machine Learning for Signal Processing

Research Statement

Making computers that understand their world around them is an incredibly hard problem. Fortunately it is also fascinating! My research explores the computational foundations for constructing systems that can understand sound (e.g., speech or music) the same way we do. On the theoretical side this involves creating new tools for processing and analyzing time-series, and draws heavily from the fields of machine learning and statistical signal processing. On the practical side this results in constructing actual machines with hearing abilities such as TVs that can find when the football game gets interesting, stethoscopes that detect and analyze heartbeats, music players that automatically DJ for you and smart traffic lights that can hear accidents that happen in their intersection. I am also interested in anything involving audio and computation and have been involved in the fields of computer music, audio synthesis algorithms and real-time performance.

Research Interests

  • Machine Learning
  • Signal Processing
  • Machine Listening
  • Audio Processing

Research Areas

  • Acoustics
  • Machine learning
  • Machine learning and pattern recognition
  • Signal detection and estimation
  • Speech processing
  • Speech recognition and processing

Teaching Honors

  • Engineering Council Outstanding Advisors (2015)
  • List of teachers ranked as excellent by their students (Fall 2015)
  • List of teachers ranked as excellent by their students (Spring 2015)
  • List of teachers ranked as excellent by their students (Fall 2014)
  • Engineering Council Outstanding Advisors (2014)
  • List of teachers ranked as excellent by their students (Spring 2014)
  • List of teachers ranked as excellent by their students (Fall 2012)
  • List of teachers ranked as excellent by their students (Fall 2011)
  • List of teachers ranked as excellent by their students (Fall 2010)

Other Honors

  • Dean’s Award for Excellence in Research (2016)
  • IEEE Signal Processing Society Distinguished Lecturer (2016-2017)
  • Adobe Distinguished Inventor (2015)
  • MIT Technology Review's World's Top 35 innovators under 35 years old (TR35) (2006)
  • C. W. Gear Outstanding Junior Faculty Award (2015)
  • IEEE Fellow (2015)

Courses Taught

  • CS 498 - Probability in CS
  • CS 598 - Mach Lrng for Signal Processng
  • ECE 310 - Digital Signal Processing
  • ECE 311 - Digital Signal Processing Lab
  • ECE 403 - Audio Engineering
  • INFO 510 - Research Practicum