Pitt Summer School on Signal Processing and Machine Learning for Big Data
The Swanson School of Engineering, in collaboration with the Institute of Electrical and Electronics Engineers (IEEE) Signal Processing Society (SPS), will host the 2016 Summer School on Signal Processing and Machine Learning for Big Data from May 17–19 (http://www.engineering.pitt.edu/ieeesps/). The 2016 Summer School at Pitt will be the first time the program is held in the United States and the second time in North America.
The Summer School will address current efforts to explore Big Data from a signal processing perspective, including Big Data applications in social networks, behavior and language analysis, bioinformatics and environmental monitoring as well as foundations for Big Data analysis and processing such as robust statistical methods, sparse representations, numerical linear algebra, machine learning, convergence and complexity analysis.
Over the course of three days, the event will feature lecturers from Carnegie Mellon University, the University of Illinois at Urbana-Champaign, the University of California in Los Angeles, Purdue University, the University of Maryland, the University of Toronto and the University of Pittsburgh. Lecturers from ANSYS, Rockwell Automation, Google and the IBM Watson project will also be in attendance and discuss the topic from an industry perspective.
For more information and to register for the event, please visit http://www.engineering.pitt.edu/ieeesps/ or https://www.regonline.com/Register/Checkin.aspx?EventID=1811061. Registration closes on April 30, and space is limited.