Dr. Ulisses Braga-Neto, associate professor in the Department of Electrical and Computer Engineering at Texas A&M University, was elected to the Machine Learning for Signal Processing Technical Committee (MLSP TC) of the Institute of Electrical and Electronics Engineers (IEEE) Signal Processing Society for the 2017-2019 term.
The committee is at the interface between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. Central to MLSP is online/adaptive nonlinear signal processing and data-driven learning methodologies. Texas A&M has been making a concerted institutional effort to be a key player in the emerging area of data analytics for complex applications, known popularly as Big Data.
“The IEEE MLSP TC is expected to play a central role in the next few years in shaping the IEEE policies and approaches to Big Data,” Braga-Neto said. “I intend to contribute to this effort via my experience in statistical pattern recognition and signal processing for genomic research. I also intend to represent and defend the interests of professionals in the area, especially those of investigators at Texas A&M.”
Braga-Neto received his Ph.D. in electrical and computer engineering from The Johns Hopkins University in 2002. He joined the Biomedical Imaging and Genomic Signal Processing group in the department in 2007. Prior to that, he was a post-doctoral researcher with the Section of Clinical Cancer Genetics at the University of Texas M.D. Anderson Cancer Center from 2002 to 2004, and an assistant researcher with the Oswaldo Cruz Foundation, Brazil, from 2004 to 2006. His honors include receiving the NSF CAREER Award in 2009. Braga-Neto’s research interests include statistical signal processing and statistical pattern recognition, with applications in the study of cancer and infectious diseases.