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School of Engineering

Shuchin Aeron

Associate Professor
Electrical and Computer Engineering
Adjunct Associate Professor, Department of Computer Science

Shuchin Aeron

Shuchin Aeron

Associate Professor
Electrical and Computer Engineering
Adjunct Associate Professor, Department of Computer Science

Phone 617-627-4653
Halligan Hall, Room 242
161 College Avenue, Medford, MA
Research: 
statistical signal processing, inverse problems, compressed sensing, information theory, convex optimization, machine learning, algorithms for geophysical signal processing, compressed sensing architectures and evaluation, video and image data acquisition and processing, bioengineering metabolic networks
Biography: 

Shuchin Aeron is an associate professor in the Department of Electrical and Computer Engineering at Tufts School of Engineering. He received his Ph.D. from Boston University in 2009. He was a postdoctoral research fellow at Schlumberger-Doll Research (SDR), where he worked on signal processing solution products for borehole acoustics. Aeron has several patents in acoustic signal processing and his proposed workflows are currently implemented in SDR’s logging while drilling tools. In 2016, he received an NSF CAREER award. Aeron is currently a senior member of the Institute of Electrical and Electronics Engineers (IEEE). His research interests are in statistical signal processing, information theory, and optimal sampling and recovery for multidimensional signals and systems.

Education: 
Ph.D., Boston University
M.S., Boston University
B.Tech., Indian Institute of Technology
Professional Experience: 
2011-present:

Department of Electrical and Computer Engineering, Tufts School of Engineering

  • 2017-present: Associate Professor
  • 2011-2017: Assistant Professor
2014-present:

Department of Computer Science, Tufts School of Engineering

  • 2017-present: Adjunct Associate Professor
  • 2014-2017: Adjunct Assistant Professor
Research Interests: 

Shuchin Aeron's research interests include technical foci: statistical signal processing (SSP), inverse problems, compressed sensing, information theory, convex optimization, and machine learning. He also studies application areas: SSP algorithms for geophysical signal processing, compressed sensing architectures and evaluation, video and image data acquisition and processing, and bioengineering-metabolic networks.

Selected Honors and Awards: 
2016: CAREER Award, National Science Foundation
2015: Appointed Senior Member, IEEE
2006: Center for Information and Systems Engineering (CISE) Award, Boston University
2009: Best Thesis Award, Boston University Department of Electrical and Computer Engineering
2009: Best Thesis Award, Boston University College of Engineering
Professional Memberships: 
Institute of Electrical and Electronics Engineers (IEEE)
Teaching/Courses Taught: 
EE-23: Linear Systems
EE-127: Information Theory
EE-229: Detection and Estimation Theory