What is he best known for?
The fields of study he is best known for:
- Electrical engineering
- Integrated circuit
- Voltage
His scientific interests lie mostly in Electronic engineering, Electrical engineering, CMOS, Integrated circuit design and Low-power electronics.
His research integrates issues of Electronic circuit, Leakage, Integrated circuit, Process variation and Efficient energy use in his study of Electronic engineering.
His biological study spans a wide range of topics, including Interconnection and Circuit design.
His Electrical engineering research includes elements of Wireless and Energy harvesting.
His research in Low-power electronics intersects with topics in Low voltage and Energy consumption.
His study looks at the relationship between Subthreshold conduction and topics such as Chip, which overlap with System on a chip.
His most cited work include:
- Near-Threshold Computing: Reclaiming Moore's Law Through Energy Efficient Integrated Circuits (629 citations)
- New paradigm of predictive MOSFET and interconnect modeling for early circuit simulation (468 citations)
- Theoretical and practical limits of dynamic voltage scaling (375 citations)
What are the main themes of his work throughout his whole career to date?
Dennis Sylvester spends much of his time researching Electronic engineering, Electrical engineering, CMOS, Voltage and Leakage.
His Electronic engineering research integrates issues from Subthreshold conduction, Electronic circuit, Efficient energy use and Low-power electronics.
His Low-power electronics study incorporates themes from Low voltage and Standby power.
His Electrical engineering research is multidisciplinary, relying on both Wireless and Energy harvesting.
As a part of the same scientific family, Dennis Sylvester mostly works in the field of CMOS, focusing on Process variation and, on occasion, Monte Carlo method.
His study in Leakage is interdisciplinary in nature, drawing from both Threshold voltage and Logic gate.
He most often published in these fields:
- Electronic engineering (55.96%)
- Electrical engineering (33.03%)
- CMOS (26.70%)
What were the highlights of his more recent work (between 2016-2021)?
- Electrical engineering (33.03%)
- Electronic engineering (55.96%)
- CMOS (26.70%)
In recent papers he was focusing on the following fields of study:
Dennis Sylvester mainly investigates Electrical engineering, Electronic engineering, CMOS, Static random-access memory and Capacitor.
His work on Voltage and Leakage as part of general Electrical engineering study is frequently linked to Temperature measurement, bridging the gap between disciplines.
His Leakage research incorporates themes from Subthreshold conduction, Biasing and Logic gate.
His Electronic engineering research incorporates elements of Voltage regulation, Successive approximation ADC, Phase-locked loop, Oversampling and Efficient energy use.
His CMOS research is multidisciplinary, incorporating perspectives in State of charge, Artificial intelligence, Energy consumption and Computer vision.
His Static random-access memory study combines topics from a wide range of disciplines, such as Transistor, Embedded system, Communication channel and Parallel computing.
Between 2016 and 2021, his most popular works were:
- Neural cache: bit-serial in-cache acceleration of deep neural networks (103 citations)
- A Subthreshold Voltage Reference With Scalable Output Voltage for Low-Power IoT Systems (72 citations)
- 14.7 A 288µW programmable deep-learning processor with 270KB on-chip weight storage using non-uniform memory hierarchy for mobile intelligence (49 citations)
In his most recent research, the most cited papers focused on:
- Electrical engineering
- Integrated circuit
- Artificial intelligence
His primary areas of study are Electrical engineering, Electronic engineering, Static random-access memory, Embedded system and Capacitor.
His Electrical engineering study frequently links to adjacent areas such as Capacitance.
His Electronic engineering study combines topics in areas such as Energy harvesting, Energy, Chip, Successive approximation ADC and Efficient energy use.
His work deals with themes such as Bit cell, Transistor and Parallel computing, which intersect with Static random-access memory.
In his study, which falls under the umbrella issue of Bit cell, Computer vision is strongly linked to CMOS.
In Capacitor, he works on issues like Magnetoresistive random-access memory, which are connected to Process variation and Non-volatile memory.
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