What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer network
- Operating system
Radu Marculescu mostly deals with Network on a chip, System on a chip, Embedded system, Energy consumption and Distributed computing.
His Network on a chip research is under the purview of Computer network.
His studies in System on a chip integrate themes in fields like Traffic analysis, Integrated circuit design, Quality of service, Reduction and Data compression.
The various areas that Radu Marculescu examines in his Embedded system study include Scheduling, Processor scheduling, Schedule, Fixed-priority pre-emptive scheduling and Computation.
Radu Marculescu has included themes like Multiprocessing, Logic synthesis, FPGA prototype and Implementation in his Energy consumption study.
His Distributed computing research is multidisciplinary, relying on both Routing, Overhead, Deterministic routing and Branch and bound.
His most cited work include:
- Outstanding Research Problems in NoC Design: System, Microarchitecture, and Circuit Perspectives (598 citations)
- Energy- and performance-aware mapping for regular NoC architectures (570 citations)
- Energy-aware mapping for tile-based NoC architectures under performance constraints (512 citations)
What are the main themes of his work throughout his whole career to date?
Radu Marculescu focuses on Network on a chip, Embedded system, Distributed computing, System on a chip and Energy consumption.
As part of the same scientific family, Radu Marculescu usually focuses on Network on a chip, concentrating on Computer architecture and intersecting with Design space exploration.
Radu Marculescu has researched Embedded system in several fields, including Fault tolerance, Power management, Efficient energy use and Multi-core processor.
His research integrates issues of Control theory and Frequency scaling in his study of Power management.
While working in this field, Radu Marculescu studies both Energy consumption and Energy management.
His research related to Network packet, Multipath routing and Link-state routing protocol might be considered part of Computer network.
He most often published in these fields:
- Network on a chip (23.57%)
- Embedded system (22.50%)
- Distributed computing (18.57%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (11.79%)
- Deep learning (6.79%)
- Distributed computing (18.57%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, Deep learning, Distributed computing, Network science and Machine learning are his primary areas of study.
His Artificial intelligence study incorporates themes from Theoretical computer science, Data mining, Metric, Energy consumption and Systems design.
The study incorporates disciplines such as Design space exploration and Turing machine in addition to Distributed computing.
His Artificial neural network research integrates issues from Convolutional neural network, Telecommunications network, Host, Computational biology and Network on a chip.
His Network on a chip research incorporates themes from Backpropagation, Support vector machine, Queueing theory, Real-time computing and Queue.
His work deals with themes such as Embedded system and Wireline, which intersect with Reduction.
Between 2015 and 2021, his most popular works were:
- On-Chip Communication Network for Efficient Training of Deep Convolutional Networks on Heterogeneous Manycore Systems (46 citations)
- Wireless NoC for VFI-Enabled Multicore Chip Design: Performance Evaluation and Design Trade-Offs (29 citations)
- Wireless NoC and Dynamic VFI Codesign: Energy Efficiency Without Performance Penalty (28 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Computer network
His primary scientific interests are in Embedded system, Artificial intelligence, Deep learning, Computer architecture and Wireless.
He combines subjects such as Control system, Scalability, Design paradigm, Multi-core processor and Reinforcement learning with his study of Embedded system.
His biological study spans a wide range of topics, including Distributed computing, Machine learning, Microbiome and Edge device.
His Computer architecture study integrates concerns from other disciplines, such as Multicore systems and Traffic analysis.
His Artificial neural network research is multidisciplinary, incorporating elements of System on a chip, Computational biology, Host and Network on a chip.
His System on a chip research is multidisciplinary, incorporating perspectives in Backpropagation and Wireline.
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