Mark Davenport (ECE) awarded the Prestigious Sloan Research Fellowship for 2017

Congratulations to Professor Mark Davenport of the School of Electrical and Computer Engineering (ECE) for being awarded the prestigious Sloan Fellowship for 2017. The following note from Steve McLaughlin, the chair of ECE, describes both the award and Mark’s efforts in this space.  Congrats Mark. 

Please join me in congratulating Mark Davenport on receiving a 2017 Sloan Research Fellowship 2017. Mark is one out of 126 U.S. and Canadian researchers, representing eight fields, to receive this award. The fellowships awarded yearly since 1955, honor early-career scholars whose achievements mark them as the next generation of scientific leaders. A full list of the 2017 Fellows may be viewed at https://sloan.org/fellowships/2017-Fellows.

davenport-squareMark received his fellowship in the area of mathematics and will use the award in support of his work in developing mathematical models and algorithms for tackling the kinds of inverse problems that arise in many common signal processing and machine learning problems as a result of incomplete data and nonlinear observations. Mark’s approach to these problems centers on the use of low-dimensional structure like sparsity and low-rank matrices to help tease the underlying information out of such limited sources of data. Applications where these kinds of problems arise range from the design of hyper-efficient sensing systems to personalized medicine and intelligent tutoring systems. Mark has been a member of the Georgia Tech ECE faculty since 2012, where he is a member of the Center for Signal and Information Processing and a founding member of the Center for Machine Learning.   

This is a tremendous honor for Mark and a great recognition of ECE’s and Georgia Tech’s strengths in signal and information processing and in machine learning. Keep up the excellent work!

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.