Professor Vagelis Papalexakis has been named a winner of the Donald G. Fink Overview Paper Award presented by the Signal Processing Society of the Institute of Electrical and Electronics Engineers, or IEEE. 

The award honors the authors of a journal article that has had substantial impact over several years on a subject related to the Signal Processing Society's technical scope.  

Papalexakis was recognized for his work as a co-author on the paper  “Tensor Decomposition for Signal Processing and Machine Learning,” published in IEEE Transactions on Signal Processing in 2017. Other researchers have since cited the paper 1,280 times, according to Google Scholar.

It was the second IEEE award Papalexakis received this academic year.

He was earlier named the winner of the 2022 Tao Li Award presented this month at the International Conference on Data Mining in Orlando, Fla. This award goes to scholars in the field of data mining and machine learning who are either in a doctoral program or received a doctoral degree less than 10 years ago.