World's Best Scientists 2026 revealed!
Luca Benini

Luca Benini

Award Badge
Computer Science
Switzerland
2026
Award Badge
Electronics and Electrical Engineering
Switzerland
2026

D-Index & Metrics

Computer Science

D-Index
128
Citations
69733
World Ranking
105
National Ranking
1

Electronics and Electrical Engineering

D-Index
126
Citations
68645
World Ranking
46
National Ranking
2

Research.com Recognitions

  • 2026 - Research.com Computer Science in Switzerland Leader Award
  • 2026 - Research.com Electronics and Electrical Engineering in Switzerland Leader Award
  • 2025 - Research.com Computer Science in Switzerland Leader Award
  • 2025 - Research.com Electronics and Electrical Engineering in Switzerland Leader Award
  • 2023 - Research.com Electronics and Electrical Engineering in Italy Leader Award
  • 2022 - Research.com Computer Science in Switzerland Leader Award
  • 2022 - Research.com Electronics and Electrical Engineering in Italy Leader Award
  • 2016 - ACM Fellow For contributions to the design of low power multi-processor systems.
  • 2010 - Member of Academia Europaea
  • 2007 - IEEE Fellow For contributions to design technologies for low power design of integrated circuits and systems

Overview

Luca Benini is affiliated with ETH Zurich in Switzerland. Their research spans several fields within computer science and engineering, with a focus on electrical and electronic engineering, hardware and architecture, computer networks and communications, computer vision and pattern recognition, and artificial intelligence.

The scientist has contributed significantly to topics including parallel computing and optimization techniques, advanced memory and neural computing, advanced neural network applications, ferroelectric and negative capacitance devices, EEG and brain-computer interfaces, interconnection networks and systems, and advanced data storage technologies.

Among recent publications, some notable papers include:

  • A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition (2020, Nature Electronics)
  • EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain-Machine Interfaces (2020, Archivio istituzionale della ricerca - Alma Mater Studiorum Università di Bologna)
  • In-memory hyperdimensional computing (2020, Nature Electronics)
  • FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things (2020, IEEE Internet of Things Journal)
  • Constrained Few-shot Class-incremental Learning (2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition - CVPR)

Frequent co-authors in Luca Benini's research include Michele Magno, Francesco Conti, Simone Benatti, Davide Rossi, and Andrea Bartolini.

The scientist has published extensively in venues such as arXiv (Cornell University), Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna), IEEE Transactions on Computers, Zenodo (CERN European Organization for Nuclear Research), and IEEE Internet of Things Journal.

Honors awarded to Luca Benini include:

  • ACM Fellow (2016), for contributions to the design of low power multi-processor systems
  • Member of Academia Europaea (2010)
  • IEEE Fellow (2007), for contributions to design technologies for low power design of integrated circuits and systems

Best Publications

  • Networks on chips: a new SoC paradigm

    L. Benini;G. De Micheli

  • A survey of design techniques for system-level dynamic power management

    L. Benini;A. Bogliolo;G. De Micheli

  • NoC synthesis flow for customized domain specific multiprocessor systems-on-chip

    D. Bertozzi;A. Jalabert;Srinivasan Murali;R. Tamhankar

  • System-level power optimization: techniques and tools

    Luca Benini;Giovanni de Micheli

  • Networks on Chips: Technology and Tools

    Giovanni De Micheli;Luca Benini

  • Xpipes: a network-on-chip architecture for gigascale systems-on-chip

    D. Bertozzi;L. Benini

  • Analysis of power consumption on switch fabrics in network routers

    Terry Tao Ye;Giovanni De Micheli;Luca Benini

  • A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition

    Ali Moin;Andy Zhou;Abbas Rahimi;Alisha Menon

  • Policy optimization for dynamic power management

    L. Benini;A. Bogliolo;G.A. Paleologo;G. De Micheli

  • Dynamic Power Management: Design Techniques and CAD Tools

    Luca Benini;Giovanni de Micheli

  • Modeling and Optimization of a Solar Energy Harvester System for Self-Powered Wireless Sensor Networks

    D. Dondi;A. Bertacchini;D. Brunelli;L. Larcher

  • Design Issues and Considerations for Low-Cost 3-D TSV IC Technology

    G Van der Plas;P Limaye;I Loi;A Mercha

  • Analysis of error recovery schemes for networks on chips

    S. Murali;T. Theocharides;N. Vijaykrishnan;M.J. Irwin

  • Near-Threshold RISC-V Core With DSP Extensions for Scalable IoT Endpoint Devices

    Michael Gautschi;Pasquale Davide Schiavone;Andreas Traber;Igor Loi

  • Asymptotic zero-transition activity encoding for address busses in low-power microprocessor-based systems

    L. Benini;G. De Micheli;E. Macii;D. Sciuto

  • Soft-to-hard vector quantization for end-to-end learning compressible representations

    Eirikur Agustsson;Fabian Mentzer;Michael Tschannen;Lukas Cavigelli

  • Activity recognition from on-body sensors: accuracy-power trade-off by dynamic sensor selection

    Piero Zappi;Clemens Lombriser;Thomas Stiefmeier;Elisabetta Farella

  • ×pipesCompiler: A Tool for Instantiating Application Specific Networks on Chip

    Antoine Jalabert;Srinivasan Murali;Luca Benini;Giovanni De Micheli

  • The Cost of Application-Class Processing: Energy and Performance Analysis of a Linux-Ready 1.7-GHz 64-Bit RISC-V Core in 22-nm FDSOI Technology

    Florian Zaruba;Luca Benini

  • Dynamic power management for nonstationary service requests

    Eui-Young Chung;L. Benini;A. Bogliolo;Yung-Hsiang Lu

  • Policy optimization for dynamic power management

    G. A. Paleologo;L. Benini;A. Bogliolo;G. De Micheli

Frequent Co-Authors

Davide Brunelli
Davide Brunelli University of Trento
G. De Micheli
G. De Micheli École Polytechnique Fédérale de Lausanne
Michele Magno
Michele Magno ETH Zurich
Davide Rossi
Davide Rossi University of Bologna
Massimo Poncino
Massimo Poncino Polytechnic University of Turin
Enrico Macii
Enrico Macii Polytechnic University of Turin
Elisabetta Farella
Elisabetta Farella Fondazione Bruno Kessler
Alberto Macii
Alberto Macii Polytechnic University of Turin
Abbas Rahimi
Abbas Rahimi IBM (United States)
David Atienza
David Atienza École Polytechnique Fédérale de Lausanne

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