What is he best known for?
The fields of study he is best known for:
- Operating system
- Central processing unit
- Artificial intelligence
Fadi J. Kurdahi mostly deals with Computer architecture, Embedded system, Parallel computing, Reduced instruction set computing and Reconfigurable computing.
Fadi J. Kurdahi combines subjects such as System on a chip, Dynamic priority scheduling, SIMD and Instruction register with his study of Computer architecture.
His Embedded system study combines topics in areas such as Data compression, Control power, Bandwidth and Pattern recognition.
His Parallel computing research is multidisciplinary, incorporating elements of Field-programmable gate array, High-level synthesis, Compiler, Decoding methods and Sequential decoding.
Fadi J. Kurdahi has included themes like Evolvable hardware, Granularity and Chip in his Reduced instruction set computing study.
The concepts of his Reconfigurable computing study are interwoven with issues in Scheduling, Processor scheduling, Two-level scheduling, Application domain and Encryption.
His most cited work include:
- MorphoSys: an integrated reconfigurable system for data-parallel and computation-intensive applications (772 citations)
- REAL: A Program for REgister ALlocation (284 citations)
- Design and Implementation of the MorphoSys Reconfigurable ComputingProcessor (148 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Embedded system, Electronic engineering, Computer architecture, Parallel computing and High-level synthesis.
His Embedded system study integrates concerns from other disciplines, such as Energy consumption, Control reconfiguration and Wireless.
His studies deal with areas such as Redundancy and Communication channel as well as Wireless.
His Electronic engineering research is multidisciplinary, incorporating perspectives in Chip and Voltage.
Fadi J. Kurdahi interconnects SIMD, Reconfigurable computing, Scheduling and Reduced instruction set computing in the investigation of issues within Computer architecture.
He has researched High-level synthesis in several fields, including Computer engineering and Engineering design process.
He most often published in these fields:
- Embedded system (26.86%)
- Electronic engineering (21.20%)
- Computer architecture (12.72%)
What were the highlights of his more recent work (between 2017-2021)?
- Memristor (4.95%)
- Crossbar switch (4.59%)
- Artificial intelligence (4.59%)
In recent papers he was focusing on the following fields of study:
Fadi J. Kurdahi focuses on Memristor, Crossbar switch, Artificial intelligence, Electronic engineering and Artificial neural network.
The Memristor study combines topics in areas such as Scalability, Resistive random-access memory, Energy consumption, Inference and Parallel computing.
His Parallel computing research incorporates elements of Scheme, Reconfigurable computing and Finite impulse response.
His work in the fields of Spice overlaps with other areas such as Matrix multiplication.
His Gradient descent research integrates issues from Computational neuroscience, Computer architecture, Hardware architecture and Computer engineering.
His research investigates the connection between Embedded system and topics such as Focus that intersect with issues in Reliability.
Between 2017 and 2021, his most popular works were:
- Modeling and Analysis of Passive Switching Crossbar Arrays (20 citations)
- Independent Component Analysis Using RRAMs (14 citations)
- Supercapacitor discharge under constant resistance, constant current and constant power loads (13 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Central processing unit
- Artificial intelligence
Fadi J. Kurdahi spends much of his time researching Crossbar switch, Memristor, Artificial neural network, Artificial intelligence and Spiking neural network.
His Crossbar switch study is concerned with the larger field of Electronic engineering.
His research in Electronic engineering intersects with topics in Voltage drop, Elmore delay and Parallel processing.
His Memristor study incorporates themes from Computer architecture, Capacitive sensing, Parasitic extraction, Transient and Inductance.
Fadi J. Kurdahi incorporates Computer architecture and Flexibility in his studies.
Within one scientific family, Fadi J. Kurdahi focuses on topics pertaining to Gradient descent under Spiking neural network, and may sometimes address concerns connected to Computational neuroscience, Computer engineering and Very-large-scale integration.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
