Research/Areas of Interest:
data science, 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
Education
- PhD, Boston University, Boston, United States, 2009
- MS, Boston University, Boston, United States, 2004
- B.Tech, Indian Institute of Technology, India, 2002
- Post Doctoral Research Scientist, Schlumberger Doll Research, Cambridge, United States, 2011
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.
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.
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.