What is he best known for?
The fields of study he is best known for:
- Operating system
- Artificial intelligence
- Programming language
Sander Stuijk mostly deals with Dataflow, Distributed computing, Synchronous Data Flow, Computational complexity theory and Parallel computing.
His Distributed computing study incorporates themes from Pareto principle, Resource allocation, Processor scheduling and Implementation.
His Synchronous Data Flow research is multidisciplinary, relying on both Algorithm design, Markov chain, Data compression and Signal processing.
In the subject of general Parallel computing, his work in Multiprocessing is often linked to Resource management, thereby combining diverse domains of study.
His biological study spans a wide range of topics, including Worst-case complexity, Worst-case execution time and Information and Computer Science.
Sander Stuijk focuses mostly in the field of Real-time computing, narrowing it down to topics relating to Benchmark and, in certain cases, Photoplethysmogram.
His most cited work include:
- Algorithmic Principles of Remote PPG (235 citations)
- Throughput Analysis of Synchronous Data Flow Graphs (234 citations)
- SDF^3: SDF For Free (231 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Dataflow, Embedded system, Parallel computing, Distributed computing and Artificial intelligence.
His Dataflow study combines topics in areas such as Model of computation and Automaton, Theoretical computer science.
He studied Embedded system and Software that intersect with Compiler.
Sander Stuijk interconnects Digital signal processing, Scheduling and Computation in the investigation of issues within Parallel computing.
His research investigates the connection between Distributed computing and topics such as Synchronous Data Flow that intersect with problems in Algorithm design.
His Artificial intelligence research incorporates themes from Photoplethysmogram, Detector and Computer vision.
He most often published in these fields:
- Dataflow (25.00%)
- Embedded system (22.22%)
- Parallel computing (18.89%)
What were the highlights of his more recent work (between 2019-2021)?
- Field-programmable gate array (6.11%)
- Artificial intelligence (14.44%)
- High Bandwidth Memory (1.11%)
In recent papers he was focusing on the following fields of study:
Sander Stuijk mostly deals with Field-programmable gate array, Artificial intelligence, High Bandwidth Memory, Computational science and Stencil.
His Field-programmable gate array research includes elements of Artificial neural network, Transfer, Real-time computing and Throughput.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Respiration rate, Machine learning, Thermography and Computer vision.
The Machine learning study combines topics in areas such as Software, Benchmark and Signal processing.
His specific area of interest is Computer vision, where he studies RGB color model.
His research in Pixel intersects with topics in Image resolution, Multi camera, Infrared and Respiration.
Between 2019 and 2021, his most popular works were:
- NERO: A Near High-Bandwidth Memory Stencil Accelerator for Weather Prediction Modeling (8 citations)
- Multi-camera infrared thermography for infant respiration monitoring. (3 citations)
- Reviewing inference performance of state-of-the-art deep learning frameworks (2 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Artificial intelligence
- Programming language
Artificial intelligence, Weather and climate, High Bandwidth Memory, Computational science and Stencil are his primary areas of study.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Infrared and Respiration.
He incorporates a variety of subjects into his writings, including Weather and climate, Field-programmable gate array, Acceleration and FLOPS.
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