Davide Rossi

Active 1996–2026

418
Papers
27,034
Citations
91
h-index
261
i10-index

Citations

Citations per year for Davide Rossi1988: 1 citations1996: 8 citations1997: 10 citations1998: 27 citations1999: 30 citations2000: 23 citations2001: 34 citations2002: 28 citations2003: 28 citations2004: 20 citations2005: 29 citations2006: 18 citations2007: 30 citations2008: 47 citations2009: 68 citations2010: 85 citations2011: 162 citations2012: 254 citations2013: 309 citations2014: 323 citations2015: 308 citations2016: 360 citations2017: 416 citations2018: 430 citations2019: 971 citations2020: 1,281 citations2021: 1,260 citations2022: 1,090 citations2023: 940 citations2024: 1,203 citations2025: 690 citations2026: 125 citations1989–1995: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 2,501 citing papers, 19.7% of this breakdownItaly: 1,457 citing papers, 11.5% of this breakdownGermany: 863 citing papers, 6.8% of this breakdownChina: 832 citing papers, 6.6% of this breakdownSwitzerland: 754 citing papers, 5.9% of this breakdownUnited Kingdom: 708 citing papers, 5.6% of this breakdownFrance: 619 citing papers, 4.9% of this breakdownSpain: 528 citing papers, 4.2% of this breakdownCanada: 340 citing papers, 2.7% of this breakdownNetherlands: 333 citing papers, 2.6% of this breakdownSweden: 260 citing papers, 2.1% of this breakdownAustralia: 244 citing papers, 1.9% of this breakdown
0%19.7%Other 25.5%

Fields

  • Medicine42.2%
  • Computer Science23%
  • Biochemistry, Genetics and Molecular Biology16.8%
  • Engineering10.4%
  • Immunology and Microbiology2.6%
  • Neuroscience1.3%
  • Other3.7%

Topics

  • Lymphoma Diagnosis and Treatment7.6%
  • Chronic Lymphocytic Leukemia Research5.9%
  • Parallel Computing and Optimization Techniques3.1%
  • Advanced Memory and Neural Computing2.6%
  • Cancer Genomics and Diagnostics2.3%
  • Multiple Myeloma Research and Treatments2.3%
  • Other76.2%

Coauthors

All papers

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  1. Enhanced detection of minimal residual disease by targeted sequencing of phased variants in circulating tumor DNA

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , - Nature Biotechnology 2021 cited by 366

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

    Authors: , , , , , , - 27th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS) 2017 cited by 209

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

    Authors: , , , , , - IEEE Transactions on Computers, IEEE Trans. Computers 2021 cited by 113

  4. Circulating Tumor DNA Measurements As Early Outcome Predictors in Diffuse Large B-Cell Lymphoma

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , - Journal of Clinical Oncology 2018 cited by 496

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

    Authors: , , , , - IEEE Journal of Solid-State Circuits, IEEE J. Solid State Circuits 2019 cited by 156

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

    Authors: , , , , , , , , , , , - IEEE Journal of Solid-State Circuits, IEEE J. Solid State Circuits 2021 cited by 99

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

    Authors: , , , , , , - IEEE 29th International Conference on Application-specific Systems, Architectures and Processors (ASAP) 2018 cited by 216

  8. PULP-NN: Accelerating Quantized Neural Networks on Parallel Ultra-Low-Power RISC-V Processors

    Authors: , , , , - Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences 2019 cited by 127

  9. Dynamic Risk Profiling Using Serial Tumor Biomarkers for Personalized Outcome Prediction

    Authors: , , , , , , , , , , , , , , , , , , , , , , - Cell 2019 cited by 239

  10. Circulating tumor DNA reveals genetics, clonal evolution, and residual disease in classical Hodgkin lymphoma

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Franco Cavalli, Emanuele Zucca, Luigi Maria Larocca, Gianluca Gaïdano, Stefan Hohaus, Carmelo Carlo‐Stella, Davide Rossi - Blood 2018 cited by 338

  11. Genomic profiling for clinical decision making in lymphoid neoplasms

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Falko Fend, Philippe Gaulard, Paolo Ghia, John G. Gribben, Olivier Hermine, Daniel J. Hodson, Eric D. Hsi, Giorgio Inghirami, Elaine S. Jaffe, Kennosuke Karube, Keisuke Kataoka, Wolfgang Hiddemann, Won Seog Kim, Rebecca L. King, Young Hyeh Ko, Ann S. LaCasce, Georg Lenz, José I. Martín‐Subero, Miguel Á. Piris, Stefania Pittaluga, Laura Pasqualucci, Leticia Quintanilla‐Martínez, Scott J. Rodig, Andreas Rosenwald, Gilles Salles, Jesús F. San Miguel, Kerry J. Savage, Laurie H. Sehn, Gianpietro Semenzato, Louis M. Staudt, Steven H. Swerdlow, Constantine S. Tam, Judith Trotman, Julie M. Vose, Oliver Weigert, Wyndham H. Wilson, Jane N. Winter, Catherine J. Wu, Pier Luigi Zinzani, Emanuele Zucca, Adam Bagg, David W. Scott - Blood 2022 cited by 161

  12. Detection of early seeding of Richter transformation in chronic lymphocytic leukemia

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Francesc Bosch, Marta Aymerich, Anna Enjuanes, Sílvia Ruiz-Gaspà, Armando López‐Guillermo, Pedro Jares, Sı́lvia Beà, Salvador Capella-Gutiérrez, Josep Lluis Gelpí, Núria López-Bigas, David Torrents, Peter J. Campbell, Marta Gut, Davide Rossi, Gianluca Gaïdano, Xosé S. Puente, Pablo M. García-Rovés, Dolors Colomer, Holger Heyn, Francesco Maura, José I. Martín‐Subero, Elı́as Campo - Nature Medicine 2022 cited by 135

  13. Inactivating mutations of acetyltransferase genes in B-cell lymphoma

    Authors: , , , , , , , , , , , , , , , , , - Nature 2011 cited by 942

  14. Distinct Hodgkin lymphoma subtypes defined by noninvasive genomic profiling

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Thomas Tousseyn, Lieselot Buedts, Richard T. Hoppe, Yasodha Natkunam, Luc‐Matthieu Fornecker, Sharon M. Castellino, Ranjana H. Advani, Davide Rossi, Ryan C. Lynch, Hervé Ghesquières, Olivier Casasnovas, David M. Kurtz, Lianna J. Marks, Michael P. Link, Marc André, Peter Vandenberghe, Christian Steidl, Maximilian Diehn, Ash A. Alizadeh - Nature 2023 cited by 108

  15. XpulpNN: Accelerating Quantized Neural Networks on RISC-V Processors Through ISA Extensions

    Authors: , , , , - Design, Automation & Test in Europe Conference & Exhibition (DATE) 2020 cited by 71

  16. Circulating Tumor DNA in Lymphoma: Principles and Future Directions

    Authors: , , , , - Blood Cancer Discovery 2021 cited by 93

  17. Genetics of Follicular Lymphoma Transformation

    Authors: , , , , , , , , , , , , , , , , , , - Cell Reports 2014 cited by 585

  18. XpulpNN: Enabling Energy Efficient and Flexible Inference of Quantized Neural Networks on RISC-V Based IoT End Nodes

    Authors: , , , , - IEEE 28th Symposium on Computer Arithmetic (ARITH) 2021 cited by 52

  19. GVSoC: A Highly Configurable, Fast and Accurate Full-Platform Simulator for RISC-V based IoT Processors

    Authors: , , , , , - IEEE 39th International Conference on Computer Design (ICCD) 2021 cited by 41

  20. A 12.4TOPS/W @ 136GOPS AI-IoT System-on-Chip with 16 RISC-V, 2-to-8b Precision-Scalable DNN Acceleration and 30%-Boost Adaptive Body Biasing

    Authors: , , , , , , , , , , , , , , , , - IEEE International Solid- State Circuits Conference (ISSCC) 2023 cited by 35

  21. Marsellus: A Heterogeneous RISC-V AI-IoT End-Node SoC With 2-8 b DNN Acceleration and 30%-Boost Adaptive Body Biasing

    Authors: , , , , , , , , , - IEEE Journal of Solid-State Circuits, IEEE J. Solid State Circuits 2023 cited by 31

  22. Genetic mechanisms of HLA-I loss and immune escape in diffuse large B cell lymphoma

    Authors: , , , , , , , , , , , , , , , , , , , - National Academy of Sciences, Proceedings of the National Academy of Sciences 2021 cited by 93

  23. The genetics of Richter syndrome reveals disease heterogeneity and predicts survival after transformation

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , - Blood 2011 cited by 377

  24. Diffuse large B-cell lymphoma genotyping on the liquid biopsy

    Authors: , , , , , , , , , , , , , , - Blood 2017 cited by 258