Vaswani, Tirthapura promoted to professors

vaswaninamrata09 Namrata Vaswani was promoted to full professor in the ECpE department. Her research interests lie at the intersection of data science and machine learning for high dimensional problems and signal and information processing. Her recent research has focused on developing provably accurate online algorithms for various high-dimensional structured data recovery problems, such as online robust principal components’ analysis (PCA), online matrix completion or online sparse matrix recovery (recursive recovery of sparse vector sequences)/dynamic compressed sensing. Vaswani and and her former graduate student Wei Lu won the 2014 Best Paper Award from IEEE Signal Processing Society for their paper “Modified-CS: Modifying Compressive Sensing for Problems with Partially Known Support,  IEEE Trans. Signal Processing, Vol. 58, No. 9, September, 2010.”

Vaswani said she is excited to be promoted.

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Srikanta Tirthapura was promoted to full professor in the ECpE Department. His research interests include foundational algorithmic and software techniques tirthapurasrikanta04for large-scale data analytics, as well as applications to cybersecurity and transportation. His research has helped settle long-standing open problems in the areas of indexing multi-dimensional data, stream processing, and routing in large wireless networks. Tirthapura’s research has been funded by grants from the National Science Foundation (NSF), Defense Advanced Projects Research Agency (DARPA), IBM Corporation and Northrop Grumman Corporation. He also has received numerous awards, such as the IBM Faculty Award and the Warren B. Boast Undergraduate Teaching Award. He has developed new courses in the areas of s

oftware tools for large-scale data, and on probabilistic methods in computer engineering.

“I am very pleased to be receiving this promotion,” Tirthapura said. “This is an encouragement to further pursue my research on foundations and applications of data analysis and be a part of this exciting time for data science.”