Teaching an Old Dog New Tricks: Data Driven Signal Processing
Recent abundance of big data, and the emergence of machine learning techniques are giving rise to new data-driven approaches to old signal processing problems. I will discuss some of these techniques, and their applications to classical problems in signal processing such as hypothesis testing, detection, etc. We then discuss our joint work with AFRL on data driven STAP radar as an example, and discuss the gains of the data driven approach and our ongoing research efforts.
This a based on joint work with Shyam Venkatasubramanian, Ali Pezeshki, Muralidhar Rangaswamy, Sandeep Gogineni, and Bosung Kang.
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https://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=m215e793e7299165d876da190007983db
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- Date: 17 Jun 2022
- Time: 12:00 PM to 01:00 PM
- All times are (UTC-04:00) Eastern Time (US & Canada)
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- Starts 12 June 2022 12:00 PM
- Ends 17 June 2022 05:00 PM
- All times are (UTC-04:00) Eastern Time (US & Canada)
- No Admission Charge
Speakers
Dr. Vahid Tarokh
Teaching an Old Dog New Tricks: Data Driven Signal Processing
Biography:
Vahid Tarokh worked at AT&T Labs-Research until 2000. From 2000-2002, he was an Associate Professor at Massachusetts Institute of Technology (MIT). In 2002, he joined Harvard University as a Hammond Vinton Hayes Senior Fellow of Electrical Engineering and Perkins Professor of Applied Mathematics. He joined joined Duke University in Jan 2018, as the Rhodes Family Professor of Electrical and Computer Engineering, Computer Science, and Mathematics and Bass Connections Endowed Professor. He was also a Gordon Moore Distinguished Research Fellow at CALTECH in 2018.
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