What is he best known for?
The fields of study he is best known for:
- Electrical engineering
- Central processing unit
- Integrated circuit
His primary areas of investigation include CMOS, Electronic engineering, Electrical engineering, Adder and Electronic circuit.
His studies deal with areas such as Key generation, Low-power electronics, Integrated circuit, Process variation and Circuit design as well as CMOS.
His Electronic engineering research is multidisciplinary, incorporating perspectives in Voltage, Robustness and Leakage.
Ram Krishnamurthy usually deals with Electrical engineering and limits it to topics linked to Random number generation and Feedback loop.
His Adder research incorporates themes from Microprocessor, Logic synthesis, 32-bit and Parallel computing.
His Electronic circuit research is multidisciplinary, relying on both Floating point, Computation and Binary number.
His most cited work include:
- Near-threshold voltage (NTV) design: opportunities and challenges (207 citations)
- A sub-130-nm conditional keeper technique (171 citations)
- 16.2 A 0.19pJ/b PVT-variation-tolerant hybrid physically unclonable function circuit for 100% stable secure key generation in 22nm CMOS (142 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Electronic engineering, CMOS, Electrical engineering, Computer hardware and Electronic circuit.
His Electronic engineering research integrates issues from Transistor, Robustness and Leakage.
Ram Krishnamurthy has included themes like Adder, Efficient energy use, Datapath and Very-large-scale integration in his CMOS study.
His Adder research includes elements of Microprocessor and Multiplexer.
His Computer hardware study integrates concerns from other disciplines, such as Artificial neural network, Reduction and Cache.
His research on Electronic circuit frequently links to adjacent areas such as Low voltage.
He most often published in these fields:
- Electronic engineering (40.70%)
- CMOS (38.25%)
- Electrical engineering (24.91%)
What were the highlights of his more recent work (between 2018-2021)?
- CMOS (38.25%)
- Computer hardware (22.81%)
- Voltage (16.14%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in CMOS, Computer hardware, Voltage, Artificial neural network and Electrical engineering.
His CMOS study combines topics in areas such as Logic gate, Efficient energy use, Chip and Parallel computing.
Ram Krishnamurthy focuses mostly in the field of Logic gate, narrowing it down to matters related to Electronic circuit and, in some cases, Energy consumption.
His research integrates issues of Electronic engineering, Binary number, Computer data storage and Memory management in his study of Chip.
In general Voltage, his work in Node is often linked to Column linking many areas of study.
His Electrical engineering study frequently links to related topics such as Power management.
Between 2018 and 2021, his most popular works were:
- A 4096-Neuron 1M-Synapse 3.8-pJ/SOP Spiking Neural Network With On-Chip STDP Learning and Sparse Weights in 10-nm FinFET CMOS (28 citations)
- An All-Digital Unified Physically Unclonable Function and True Random Number Generator Featuring Self-Calibrating Hierarchical Von Neumann Extraction in 14-nm Tri-gate CMOS (18 citations)
- Why Compete When You Can Work Together: FPGA-ASIC Integration for Persistent RNNs (14 citations)
In his most recent research, the most cited papers focused on:
- Electrical engineering
- Central processing unit
- Integrated circuit
Ram Krishnamurthy focuses on Voltage, Computer hardware, Efficient energy use, Memory array and Artificial intelligence.
His work deals with themes such as CMOS, Ideal and Porting, which intersect with Voltage.
The various areas that Ram Krishnamurthy examines in his Computer hardware study include Artificial neural network, Software implementation and Range.
The concepts of his Efficient energy use study are interwoven with issues in Floating point, Binary neural network, Electronic engineering and Chip.
His Memory array study results in a more complete grasp of Electrical engineering.
With his scientific publications, his incorporates both Electrical engineering and Charge.
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