Topic
- Computing and Processing
- Components, Circuits, Devices and Systems
- Communication, Networking and Broadcast Technologies
- Power, Energy and Industry Applications
- Signal Processing and Analysis
- Robotics and Control Systems
- General Topics for Engineers
- Fields, Waves and Electromagnetics
- Engineered Materials, Dielectrics and Plasmas
- Bioengineering
- Transportation
- Photonics and Electrooptics
- Engineering Profession
- Aerospace
- Geoscience
- Nuclear Engineering
- Career Development
- Emerging Technologies
- Telecommunications
- English for Technical Professionals
David Blaauw
Also published under:D. Blaauw, D. T. Blaauw, Davidi Blaauw, David T. Blaauw, David B. Blaauw
Affiliation
Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
Topic
Energy Efficiency,Power Consumption,Clock Frequency,Neural Network,Convolutional Neural Network,Datapath,Convolutional Layers,Energy Consumption,Wireless,Fast Fourier Transform,Fully-connected Layer,Instruction Set Architecture,Neural Engineering,Power Overhead,Pulse Width,Analog-to-digital Converter,Application Programming Interface,Artificial Neural Network,Bit-width,Caching,Change Detection,Charge Pump,Dynamic Power,Electrode,Electrostatic Forces,Energy Harvesting,Feature Maps,Functional Unit,Gated Recurrent Unit,Hardware Accelerators,High Voltage,ImageNet,Impedance,Inductive Load,Keyword Spotting,Load Data,Low Power,Low Power Consumption,Low-noise Amplifier,Low-pass,Matrix Multiplication,Moore’s Law,Negative Voltage,Neural Network Classifier,Neural Network Processing,Non-volatile Memory,Non-zero Weights,Optical Power,Optical Receiver,Parasitic Capacitance,
Biography
David Blaauw (Fellow, IEEE) received the B.S. degree in physics and computer science from Duke University, Durham, NC, USA, in 1986, and the Ph.D. degree in computer science from the University of Illinois at Urbana–Champaign, Champaign, IL, USA, in 1991.
Until August 2001, he worked for Motorola, Inc., Austin, TX, USA, where he was the Manager of the High Performance Design Technology Group and received the Motorola Innovation Award. Since August 2001, he has been on the faculty of the University of Michigan, Ann Arbor, MI, USA, where he is currently the Kensall D. Wise Collegiate Professor of EECS. He has authored more than 600 articles, has received numerous best paper awards, and holds 65 patents. He has researched ultralow-power wireless sensors using subthreshold operation and low-power analog circuit techniques for millimeter systems. This research was awarded the MIT Technology Review’s “One of the Year’s Most Significant Innovations.” His research group introduced the so-called near-threshold computing, which has become a common concept in semiconductor design. Most recently, he has pursued research in cognitive computing using analog, in-memory neural networks for edge devices and genomics for precision health.
Dr. Blaauw received the 2016 SIA-SRC Faculty Award for lifetime research contributions to the U.S. semiconductor industry. He was the General Chair for the IEEE International Symposium on Low Power and a member of the IEEE International Solid-State Circuits Conference (ISSCC) Analog Program Subcommittee.
Until August 2001, he worked for Motorola, Inc., Austin, TX, USA, where he was the Manager of the High Performance Design Technology Group and received the Motorola Innovation Award. Since August 2001, he has been on the faculty of the University of Michigan, Ann Arbor, MI, USA, where he is currently the Kensall D. Wise Collegiate Professor of EECS. He has authored more than 600 articles, has received numerous best paper awards, and holds 65 patents. He has researched ultralow-power wireless sensors using subthreshold operation and low-power analog circuit techniques for millimeter systems. This research was awarded the MIT Technology Review’s “One of the Year’s Most Significant Innovations.” His research group introduced the so-called near-threshold computing, which has become a common concept in semiconductor design. Most recently, he has pursued research in cognitive computing using analog, in-memory neural networks for edge devices and genomics for precision health.
Dr. Blaauw received the 2016 SIA-SRC Faculty Award for lifetime research contributions to the U.S. semiconductor industry. He was the General Chair for the IEEE International Symposium on Low Power and a member of the IEEE International Solid-State Circuits Conference (ISSCC) Analog Program Subcommittee.