Full Name
Dr. Ethan Farquhar PhD
Job Title
Division Director, Advanced Technology and Analysis Division
Company
Savannah River National Laboratory
Speaker Bio
Dr. Ethan Farquhar started his career as a neuromorphic analog integrated circuit designer. His interests include investigating how the brain performs computations and mimicking those behaviors in low-power circuits. More recently, however, his interests have expanded to include much of the breadth of field-deployable electronic systems due to his interests in extremely low-power computational systems. This includes electronics circuit design, hardware design and layout, firmware and software design and implementations, and communications with more traditional equipment through various channels (wired, wireless, satellite, etc.).
He has extensive experience with embedded system design, leading teams of embedded designers at Oak Ridge National Laboratory and now at Pacific Northwest National Laboratory. He has designed embedded systems that collect and process data for a wide variety of applications including everything from 3D movement data for amputee patients to systems used for nuclear treaty verification purposes. His interest in neuromorphic computing has influenced the work he has done since. While not a primary focus, he has been involved in machine learning work (while at ORNL), including leading the development of a software tool that utilized differential evolution and Kernel-base regression techniques for classifying streaming data.
He has extensive experience with embedded system design, leading teams of embedded designers at Oak Ridge National Laboratory and now at Pacific Northwest National Laboratory. He has designed embedded systems that collect and process data for a wide variety of applications including everything from 3D movement data for amputee patients to systems used for nuclear treaty verification purposes. His interest in neuromorphic computing has influenced the work he has done since. While not a primary focus, he has been involved in machine learning work (while at ORNL), including leading the development of a software tool that utilized differential evolution and Kernel-base regression techniques for classifying streaming data.
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