What is he best known for?
The fields of study he is best known for:
- Operating system
- Artificial intelligence
- Computer network
Mehrdad Nourani focuses on Electronic engineering, System on a chip, Built-in self-test, System testing and Signal integrity.
In general Electronic engineering study, his work on Logic synthesis often relates to the realm of Dissipation, thereby connecting several areas of interest.
His System on a chip research is classified as research in Embedded system.
In his study, Automatic test pattern generation, Computer hardware and Test compression is inextricably linked to Design for testing, which falls within the broad field of Embedded system.
The Built-in self-test study combines topics in areas such as Energy consumption, Algorithm, Reduction and Shift register.
In Feature extraction, Mehrdad Nourani works on issues like Adaptive filter, which are connected to Artificial intelligence.
His most cited work include:
- A Motion-Tolerant Adaptive Algorithm for Wearable Photoplethysmographic Biosensors (153 citations)
- Progress and challenges in intelligent vehicle area networks (151 citations)
- Nine-coded compression technique for testing embedded cores in SoCs (132 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Electronic engineering, Artificial intelligence, Embedded system, Feature extraction and Pattern recognition.
His Electronic engineering research includes themes of Transistor, Digital electronics and Electrical engineering.
His Artificial intelligence research integrates issues from Machine learning, Computer vision and Electroencephalography.
In the field of Embedded system, his study on System on a chip overlaps with subjects such as System testing.
His biological study spans a wide range of topics, including Signal integrity, Automatic test pattern generation and Integer programming.
His Feature extraction research is multidisciplinary, relying on both Fault, Speech recognition, Wavelet transform and Signal processing.
He most often published in these fields:
- Electronic engineering (22.66%)
- Artificial intelligence (16.80%)
- Embedded system (14.84%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (16.80%)
- Feature extraction (9.77%)
- Pattern recognition (8.20%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Feature extraction, Pattern recognition, Electroencephalography and Cluster analysis.
His studies deal with areas such as Machine learning and Computer vision as well as Artificial intelligence.
His Feature extraction study integrates concerns from other disciplines, such as Cross-validation, Signal processing, Fault and Wavelet, Wavelet transform.
His study in the field of Class also crosses realms of Dimension.
His work on Epileptic seizure is typically connected to Personalization as part of general Electroencephalography study, connecting several disciplines of science.
Mehrdad Nourani focuses mostly in the field of Frequency domain, narrowing it down to topics relating to Speech recognition and, in certain cases, Dimensionality reduction.
Between 2014 and 2021, his most popular works were:
- Multi-Biosignal Analysis for Epileptic Seizure Monitoring. (56 citations)
- Automated seizure detection using limited-channel EEG and non-linear dimension reduction (42 citations)
- A Non-EEG Biosignals Dataset for Assessment and Visualization of Neurological Status (37 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Computer network
Mehrdad Nourani mostly deals with Artificial intelligence, Feature extraction, Fault, Electroencephalography and Pattern recognition.
His Artificial intelligence research incorporates elements of Machine learning, Speech recognition, Computer vision and Identification.
His study explores the link between Feature extraction and topics such as Frequency domain that cross with problems in Dimensionality reduction, Acoustic emission, Wavelet transform and Wavelet.
Mehrdad Nourani interconnects Algorithm, Electronic engineering, Power MOSFET and Signal in the investigation of issues within Fault.
The study incorporates disciplines such as Estimator and Condition monitoring in addition to Electronic engineering.
Many of his research projects under Electroencephalography are closely connected to Dimension with Dimension, tying the diverse disciplines of science together.
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