What is he best known for?
The fields of study he is best known for:
- Electrical engineering
- Semiconductor
- Transistor
His scientific interests lie mostly in Optoelectronics, CMOS, Electronic engineering, Silicon and MOSFET.
His Optoelectronics research incorporates elements of Transistor, Voltage, Semiconductor device and Nanotechnology.
CMOS is a subfield of Electrical engineering that Ru Huang investigates.
The various areas that Ru Huang examines in his Electronic engineering study include Surface finish, Operational amplifier, Skin effect, Equivalent circuit and Nanoelectronics.
The Silicon study combines topics in areas such as Substrate, Gate dielectric and Quantum tunnelling.
His studies in MOSFET integrate themes in fields like Parasitic capacitance, Capacitance, Parasitic element, Silicon on insulator and Infrasound.
His most cited work include:
- A 0.4-V Low Noise Amplifier Using Forward Body Bias Technology for 5 GHz Application (83 citations)
- Analog/RF Performance of Si Nanowire MOSFETs and the Impact of Process Variation (80 citations)
- Investigation of Low-Frequency Noise in Silicon Nanowire MOSFETs (64 citations)
What are the main themes of his work throughout his whole career to date?
Ru Huang mainly focuses on Optoelectronics, Electronic engineering, Electrical engineering, CMOS and Transistor.
The concepts of his Optoelectronics study are interwoven with issues in Field-effect transistor, Layer and MOSFET.
His Electronic engineering study incorporates themes from Noise and Reliability.
Ru Huang interconnects Electronic circuit, Doping and Integrated circuit in the investigation of issues within CMOS.
The study incorporates disciplines such as Communication channel and Quantum tunnelling in addition to Transistor.
His Silicon study combines topics in areas such as Nanowire, Nanotechnology and Annealing.
He most often published in these fields:
- Optoelectronics (54.47%)
- Electronic engineering (25.17%)
- Electrical engineering (22.83%)
What were the highlights of his more recent work (between 2017-2021)?
- Optoelectronics (54.47%)
- Electronic engineering (25.17%)
- Neuromorphic engineering (4.26%)
In recent papers he was focusing on the following fields of study:
Ru Huang mainly investigates Optoelectronics, Electronic engineering, Neuromorphic engineering, Resistive random-access memory and Artificial neural network.
His study in the field of Silicon is also linked to topics like Degradation.
In his work, Circuit design is strongly intertwined with Electronic circuit, which is a subfield of Electronic engineering.
His work deals with themes such as Computer architecture and Memristor, which intersect with Neuromorphic engineering.
His work carried out in the field of Resistive random-access memory brings together such families of science as Tin and Resistive touchscreen.
His Transistor research incorporates themes from Electron mobility and Indium tin oxide.
Between 2017 and 2021, his most popular works were:
- A comprehensive review on emerging artificial neuromorphic devices (63 citations)
- Probing memristive switching in nanoionic devices (62 citations)
- Brain-inspired computing with memristors: Challenges in devices, circuits, and systems (36 citations)
In his most recent research, the most cited papers focused on:
- Electrical engineering
- Semiconductor
- Transistor
His primary areas of investigation include Optoelectronics, Memristor, Electronic engineering, Artificial neural network and Circuit design.
His Optoelectronics research includes themes of Field-effect transistor and Resistive random-access memory, Voltage.
His study in Memristor is interdisciplinary in nature, drawing from both Neuromorphic engineering, Adder, Nanotechnology and Arithmetic.
His Electronic engineering study combines topics from a wide range of disciplines, such as Characterization, Transistor, Resistive switching and High spatial resolution.
His biological study spans a wide range of topics, including Electronic circuit and Statistical physics.
His study looks at the intersection of Electronic circuit and topics like Reliability with Statistical static timing analysis and CMOS.
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