World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
5134
World Ranking
10858
National Ranking
343

Overview

Davide Rossi is affiliated with the University of Bologna in Italy. Their research contributions primarily span the fields of Computer Science and Engineering, with a strong emphasis on Electrical and Electronic Engineering and Hardware and Architecture.

The scientist's work centers on several specialized subfields, including:

  • Electrical and Electronic Engineering
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

Main topics addressed in their research include:

  • Parallel Computing and Optimization Techniques
  • Advanced Memory and Neural Computing
  • Embedded Systems Design Techniques
  • Ferroelectric and Negative Capacitance Devices
  • CCD and CMOS Imaging Sensors
  • Low-power high-performance VLSI design
  • Interconnection Networks and Systems

Davide Rossi has contributed to multiple publication venues, notably:

  • arXiv (Cornell University)
  • IEEE Transactions on Circuits and Systems I Regular Papers
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • IEEE Journal of Solid-State Circuits
  • Balneo and PRM Research Journal

Frequent co-authors collaborating with Rossi include:

  • Luca Benini
  • Francesco Conti
  • Angelo Garofalo
  • Giuseppe Tagliavini
  • Yvan Tortorella

Selected recent publications by Davide Rossi encompass:

  • "Vega: A Ten-Core SoC for IoT Endnodes With DNN Acceleration and Cognitive Wake-Up From MRAM-Based State-Retentive Sleep Mode," 2021, IEEE Journal of Solid-State Circuits
  • "Arnold: An eFPGA-Augmented RISC-V SoC for Flexible and Low-Power IoT End Nodes," 2021, Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna)
  • "XpulpNN: Enabling Energy Efficient and Flexible Inference of Quantized Neural Networks on RISC-V Based IoT End Nodes," 2021, IEEE Transactions on Emerging Topics in Computing
  • "A Heterogeneous In-Memory Computing Cluster for Flexible End-to-End Inference of Real-World Deep Neural Networks," 2022, IEEE Journal on Emerging and Selected Topics in Circuits and Systems
  • "Always-On 674μ W@4GOP/s Error Resilient Binary Neural Networks With Aggressive SRAM Voltage Scaling on a 22-nm IoT End-Node," 2020, IEEE Transactions on Circuits and Systems I Regular Papers

Best Publications

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

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

  • YodaNN: An Architecture for Ultralow Power Binary-Weight CNN Acceleration

    Renzo Andri;Lukas Cavigelli;Davide Rossi;Luca Benini

  • YodaNN: An Ultra-Low Power Convolutional Neural Network Accelerator Based on Binary Weights

    Renzo Andri;Lukas Cavigelli;Davide Rossi;Luca Benini

  • Slow and steady wins the race? A comparison of ultra-low-power RISC-V cores for Internet-of-Things applications

    Pasquale Davide Schiavone;Francesco Conti;Davide Rossi;Michael Gautschi

  • GAP-8: A RISC-V SoC for AI at the Edge of the IoT

    Eric Flamand;Davide Rossi;Francesco Conti;Igor Loi

  • Coordinating multiagent applications on the WWW: a reference architecture

    P. Ciancarini;R. Tolksdorf;F. Vitali;D. Rossi

  • Mr.Wolf: An Energy-Precision Scalable Parallel Ultra Low Power SoC for IoT Edge Processing

    Antonio Pullini;Davide Rossi;Igor Loi;Giuseppe Tagliavini

  • Jada - Coordination and Communication for Java Agents

    Paolo Ciancarini;Davide Rossi

  • PULP: A parallel ultra low power platform for next generation IoT applications

    Davide Rossi;Francesco Conti;Andrea Marongiu;Antonio Pullini

  • A transprecision floating-point platform for ultra-low power computing

    Giuseppe Tagliavini;Stefan Mach;Davide Rossi;Andrea Marongiu

  • An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

    Francesco Conti;Robert Schilling;Pasquale Davide Schiavone;Antonio Pullini

  • PULP: A Ultra-Low Power Parallel Accelerator for Energy-Efficient and Flexible Embedded Vision

    Francesco Conti;Davide Rossi;Antonio Pullini;Igor Loi

  • DORY: Automatic End-to-End Deployment of Real-World DNNs on Low-Cost IoT MCUs

    Alessio Burrello;Angelo Garofalo;Nazareno Bruschi;Giuseppe Tagliavini

  • Vega: A Ten-Core SoC for IoT Endnodes With DNN Acceleration and Cognitive Wake-Up From MRAM-Based State-Retentive Sleep Mode

    Davide Rossi;Francesco Conti;Manuel Eggimann;Alfio Di Mauro

  • SLA-Driven Clustering of QoS-Aware Application Servers

    Unknown

  • Neurostream: Scalable and Energy Efficient Deep Learning with Smart Memory Cubes

    Erfan Azarkhish;Davide Rossi;Igor Loi;Luca Benini

  • A Heterogeneous Digital Signal Processor for Dynamically Reconfigurable Computing

    Davide Rossi;Fabio Campi;Simone Spolzino;Stefano Pucillo

  • PULP-NN: accelerating quantized neural networks on parallel ultra-low-power RISC-V processors

    Angelo Garofalo;Manuele Rusci;Francesco Conti;Francesco Conti;Davide Rossi

  • Quentin: an Ultra-Low-Power PULPissimo SoC in 22nm FDX

    Pasquale Davide Schiavone;Davide Rossi;Antonio Pullini;Alfio Di Mauro

  • Online Learning and Classification of EMG-Based Gestures on a Parallel Ultra-Low Power Platform Using Hyperdimensional Computing

    Simone Benatti;Fabio Montagna;Victor Kartsch;Abbas Rahimi

  • A 60 GOPS/W, −1.8 V to 0.9 V body bias ULP cluster in 28 nm UTBB FD-SOI technology

    Davide Rossi;Antonio Pullini;Igor Loi;Michael Gautschi

  • Tuple-based Technologies for Coordination

    Unknown

  • The ShaPE of ShaDe: a Coordination System

    S. Castellani;P. Ciancarini;D. Rossi

  • NEURAghe: Exploiting CPU-FPGA Synergies for Efficient and Flexible CNN Inference Acceleration on Zynq SoCs

    Paolo Meloni;Alessandro Capotondi;Gianfranco Deriu;Michele Brian

  • A sensor fusion approach for drowsiness detection in wearable ultra-low-power systems

    Victor Javier Kartsch;Simone Benatti;Pasquale Davide Schiavone;Davide Rossi

  • Energy-Efficient Near-Threshold Parallel Computing: The PULPv2 Cluster

    Davide Rossi;Antonio Pullini;Igor Loi;Michael Gautschi

  • Arnold: An eFPGA-Augmented RISC-V SoC for Flexible and Low-Power IoT End Nodes

    Pasquale Davide Schiavone;Davide Rossi;Alfio Di Mauro;Frank K. Gurkaynak

  • XpulpNN: accelerating quantized neural networks on RISC-V processors through ISA extensions

    Angelo Garofalo;Giuseppe Tagliavini;Francesco Conti;Davide Rossi

  • YodaNN: An Architecture for Ultra-Low Power Binary-Weight CNN Acceleration

    Renzo Andri;Lukas Cavigelli;Davide Rossi;Luca Benini

  • A near-threshold RISC-V core with DSP extensions for scalable IoT Endpoint Devices

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

Frequent Co-Authors

Luca Benini
Luca Benini ETH Zurich
Elisabetta Farella
Elisabetta Farella Fondazione Bruno Kessler
Andreas Burg
Andreas Burg École Polytechnique Fédérale de Lausanne
David Atienza
David Atienza École Polytechnique Fédérale de Lausanne
Paolo Ciancarini
Paolo Ciancarini University of Bologna
Pierpaolo Palestri
Pierpaolo Palestri University of Udine
Roberto Guerrieri
Roberto Guerrieri University of Bologna
Qiuting Huang
Qiuting Huang ETH Zurich
Marco Brambilla
Marco Brambilla Polytechnic University of Milan
Rolf Ernst
Rolf Ernst Technische Universität Braunschweig

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA opens doors to many related degrees and flexible learning paths. Many students prefer online study options that help them balance school, work, and personal life. Enrolling in the quickest masters degree online can help you earn an advanced credential in less time, making it easier to start or accelerate your career.

If you’re wondering which programs bring the best return on your investment, consider the most useful graduate degrees. These degrees are in high demand and can enhance job prospects or earning potential in the tech sector and beyond.

For those seeking a more affordable or flexible starting point, an online associate degree provides foundational skills and a pathway into the industry. There are also several affordable online degree programs to reduce tuition costs, making a quality education accessible to more students.

Whether you’re aiming for an associate, bachelor’s, or master’s, online programs offer a range of options in Computer Science and related fields to fit your career goals and budget.

Best Scientists Citing Davide Rossi

Trending Scientists

Recently Published Articles