Massimo Giordano

1.4k total citations · 1 hit paper
11 papers, 959 citations indexed

About

Massimo Giordano is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Cellular and Molecular Neuroscience. According to data from OpenAlex, Massimo Giordano has authored 11 papers receiving a total of 959 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Electrical and Electronic Engineering, 4 papers in Computer Vision and Pattern Recognition and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Massimo Giordano's work include Advanced Memory and Neural Computing (10 papers), Ferroelectric and Negative Capacitance Devices (9 papers) and Advanced Neural Network Applications (4 papers). Massimo Giordano is often cited by papers focused on Advanced Memory and Neural Computing (10 papers), Ferroelectric and Negative Capacitance Devices (9 papers) and Advanced Neural Network Applications (4 papers). Massimo Giordano collaborates with scholars based in United States, Switzerland and Taiwan. Massimo Giordano's co-authors include Stefano Ambrogio, Pritish Narayanan, Geoffrey W. Burr, Hsinyu Tsai, R. M. Shelby, Benjamin D. Killeen, Severin Sidler, Carmelo di Nolfo, Irem Boybat and Robert M. Radway and has published in prestigious journals such as Nature, Journal of Applied Physics and IEEE Journal of Solid-State Circuits.

In The Last Decade

Massimo Giordano

11 papers receiving 939 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Equivalent-accuracy accelerated neural-network training using analogue memory

2018 770 citations Stefano Ambrogio, Pritish Narayanan et al. Nature profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Massimo Giordano United States	8	911	251	237	125	116	11	959
Weier Wan United States	9	877 1.0×	229 0.9×	204 0.9×	110 0.9×	106 0.9×	16	947
Yimao Cai China	20	1.1k 1.2×	359 1.4×	171 0.7×	93 0.7×	154 1.3×	109	1.2k
Liying Xu China	12	842 0.9×	268 1.1×	298 1.3×	164 1.3×	164 1.4×	24	917
Ligang Gao United States	16	1.1k 1.2×	420 1.7×	144 0.6×	133 1.1×	121 1.0×	33	1.1k
Alessandro Fumarola Switzerland	10	1.0k 1.1×	328 1.3×	226 1.0×	164 1.3×	158 1.4×	11	1.1k
Caidie Cheng China	11	665 0.7×	175 0.7×	264 1.1×	134 1.1×	138 1.2×	14	724
Rajkumar Kubendran United States	9	723 0.8×	212 0.8×	146 0.6×	101 0.8×	64 0.6×	26	808
I‐Ting Wang Taiwan	17	1.2k 1.3×	497 2.0×	160 0.7×	109 0.9×	156 1.3×	44	1.3k
Roberto Carboni Italy	13	953 1.0×	436 1.7×	145 0.6×	243 1.9×	62 0.5×	16	1.0k

Countries citing papers authored by Massimo Giordano

Since Specialization

Citations

This map shows the geographic impact of Massimo Giordano's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Massimo Giordano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Giordano more than expected).

Fields of papers citing papers by Massimo Giordano

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Massimo Giordano. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Massimo Giordano. The network helps show where Massimo Giordano may publish in the future.

Co-authorship network of co-authors of Massimo Giordano

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Giordano. A scholar is included among the top collaborators of Massimo Giordano based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Massimo Giordano. Massimo Giordano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

Radway, Robert M., Massimo Giordano, Win-San Khwa, et al.. (2025). MINOTAUR: A Posit-Based 0.42–0.50-TOPS/W Edge Transformer Inference and Training Accelerator. IEEE Journal of Solid-State Circuits. 60(4). 1311–1323. 1 indexed citations

Radway, Robert M., Massimo Giordano, Win-San Khwa, et al.. (2024). MINOTAUR: An Edge Transformer Inference and Training Accelerator with 12 MBytes On-Chip Resistive RAM and Fine-Grained Spatiotemporal Power Gating. 1–2. 3 indexed citations

Giordano, Massimo, et al.. (2024). TinyForge: A Design Space Exploration to Advance Energy and Silicon Area Trade-offs in tinyML Compute Architectures with Custom Latch Arrays. 1033–1047. 2 indexed citations

Radway, Robert M., Massimo Giordano, Rohan Doshi, et al.. (2022). CHIMERA: A 0.92-TOPS, 2.2-TOPS/W Edge AI Accelerator With 2-MByte On-Chip Foundry Resistive RAM for Efficient Training and Inference. IEEE Journal of Solid-State Circuits. 57(4). 1013–1026. 39 indexed citations

Giordano, Massimo, Robert M. Radway, Rohan Doshi, et al.. (2021). CHIMERA: A 0.92 TOPS, 2.2 TOPS/W Edge AI Accelerator with 2 MByte On-Chip Foundry Resistive RAM for Efficient Training and Inference. 1–2. 35 indexed citations

Yu, Wei-Han, Massimo Giordano, Rohan Doshi, et al.. (2021). A 4-bit Mixed-Signal MAC Array with Swing Enhancement and Local Kernel Memory. 326–329. 8 indexed citations

Giordano, Massimo, Koji Ishibashi, Stefano Ambrogio, et al.. (2019). Analog-to-Digital Conversion With Reconfigurable Function Mapping for Neural Networks Activation Function Acceleration. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 9(2). 367–376. 21 indexed citations

Hsieh, E. R., Massimo Giordano, Robert M. Radway, et al.. (2019). High-Density Multiple Bits-per-Cell 1T4R RRAM Array with Gradual SET/RESET and its Effectiveness for Deep Learning. 35.6.1–35.6.4. 39 indexed citations

Ambrogio, Stefano, Pritish Narayanan, Hsinyu Tsai, et al.. (2018). Equivalent-accuracy accelerated neural-network training using analogue memory. Nature. 558(7708). 60–67. 770 indexed citations breakdown →

10.

Giordano, Massimo, Stefano Ambrogio, Pritish Narayanan, et al.. (2018). Perspective on training fully connected networks with resistive memories: Device requirements for multiple conductances of varying significance. Journal of Applied Physics. 124(15). 28 indexed citations

11.

Ambrogio, Stefano, Massimo Giordano, Pritish Narayanan, et al.. (2018). Training fully connected networks with resistive memories: impact of device failures. Faraday Discussions. 213(0). 371–391. 13 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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