Matthew Marinella

6.8k total citations · 3 hit papers
166 papers, 5.4k citations indexed

About

Matthew Marinella is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Artificial Intelligence. According to data from OpenAlex, Matthew Marinella has authored 166 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 163 papers in Electrical and Electronic Engineering, 27 papers in Cellular and Molecular Neuroscience and 21 papers in Artificial Intelligence. Recurrent topics in Matthew Marinella's work include Advanced Memory and Neural Computing (114 papers), Semiconductor materials and devices (71 papers) and Ferroelectric and Negative Capacitance Devices (59 papers). Matthew Marinella is often cited by papers focused on Advanced Memory and Neural Computing (114 papers), Semiconductor materials and devices (71 papers) and Ferroelectric and Negative Capacitance Devices (59 papers). Matthew Marinella collaborates with scholars based in United States, Spain and Japan. Matthew Marinella's co-authors include Sapan Agarwal, A. Alec Talin, Elliot J. Fuller, Alberto Salleo, Scott T. Keene, Conrad D. James, Gregório Couto Faria, Yoeri van de Burgt, Andrew J. Lohn and Steven J. Plimpton and has published in prestigious journals such as Science, Advanced Materials and Nature Materials.

In The Last Decade

Matthew Marinella

152 papers receiving 5.3k citations

Hit Papers

A non-volatile organic electrochemical device as a low-vo... 2016 2026 2019 2022 2017 2019 2016 400 800 1.2k
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.

  1. A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing
    2017 1.5k citations Elliot J. Fuller, Sapan Agarwal et al. profile →
  2. Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing
    2019 598 citations Elliot J. Fuller, Sapan Agarwal et al. profile →
  3. Li‐Ion Synaptic Transistor for Low Power Analog Computing
    2016 504 citations Elliot J. Fuller, Sapan Agarwal et al. Advanced Materials profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew Marinella United States 31 5.1k 1.8k 1.3k 784 586 166 5.4k
Sapan Agarwal United States 22 3.8k 0.7× 1.4k 0.8× 1.1k 0.9× 594 0.8× 548 0.9× 89 4.2k
Elliot J. Fuller United States 19 3.8k 0.7× 1.5k 0.8× 1.3k 1.0× 519 0.7× 566 1.0× 56 4.1k
Yoeri van de Burgt Netherlands 23 3.8k 0.7× 1.7k 0.9× 1.9k 1.5× 466 0.6× 563 1.0× 43 4.6k
Changhwan Choi South Korea 38 3.8k 0.8× 1.2k 0.7× 753 0.6× 320 0.4× 1.2k 2.0× 154 4.2k
Bipin Rajendran United States 27 4.3k 0.8× 1.1k 0.6× 571 0.5× 830 1.1× 1.3k 2.2× 105 5.0k
Themis Prodromakis United Kingdom 39 5.0k 1.0× 2.6k 1.5× 726 0.6× 440 0.6× 613 1.0× 228 6.0k
Feichi Zhou China 22 3.3k 0.7× 1.1k 0.6× 750 0.6× 612 0.8× 1.1k 1.9× 55 4.0k
Zhiyong Li United States 21 5.4k 1.1× 2.6k 1.4× 871 0.7× 728 0.9× 541 0.9× 70 5.7k
Guangdong Zhou China 43 4.5k 0.9× 1.9k 1.0× 1.7k 1.4× 319 0.4× 919 1.6× 157 5.3k
Armantas Melianas Sweden 31 3.4k 0.7× 1.0k 0.6× 1.9k 1.5× 301 0.4× 341 0.6× 43 3.7k

Countries citing papers authored by Matthew Marinella

Since Specialization
Citations

This map shows the geographic impact of Matthew Marinella'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 Matthew Marinella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Marinella more than expected).

Fields of papers citing papers by Matthew Marinella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew Marinella. 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 Matthew Marinella. The network helps show where Matthew Marinella may publish in the future.

Co-authorship network of co-authors of Matthew Marinella

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Marinella. A scholar is included among the top collaborators of Matthew Marinella 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 Matthew Marinella. Matthew Marinella is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Xiao, T. Patrick, Donald A. Wilson, Christopher H. Bennett, et al.. (2025). In Situ Analog In-Memory Computing Under Ionizing Radiation Exposure. IEEE Transactions on Nuclear Science. 72(4). 1243–1251.
2.
Bennett, Christopher R., T. Patrick Xiao, Dennis Wilson, et al.. (2023). TID Response of an Analog In-Memory Neural Network Accelerator. 1–6. 1 indexed citations
3.
Xiao, T. Patrick, Donald A. Wilson, Christopher H. Bennett, et al.. (2023). Total Ionizing Dose Response of 128 Analog States in Computational Charge-Trap Memory. IEEE Transactions on Nuclear Science. 71(4). 446–453. 3 indexed citations
4.
Bennett, Christopher H., Felipe García‐Sánchez, Matthew Marinella, et al.. (2023). High-speed CMOS-free purely spintronic asynchronous recurrent neural network. SHILAP Revista de lepidopterología. 1(1). 3 indexed citations
5.
Robinson, D., Michael E. Foster, Christopher H. Bennett, et al.. (2022). Tunable Intervalence Charge Transfer in Ruthenium Prussian Blue Analog Enables Stable and Efficient Biocompatible Artificial Synapses. Advanced Materials. 35(37). e2207595–e2207595. 15 indexed citations
6.
Xiao, T. Patrick, et al.. (2022). An Accurate, Error-Tolerant, and Energy-Efficient Neural Network Inference Engine Based on SONOS Analog Memory. IEEE Transactions on Circuits and Systems I Regular Papers. 69(4). 1480–1493. 17 indexed citations
7.
Ashby, David S., György Vizkelethy, Matthew Marinella, et al.. (2021). Identification of localized radiation damage in power MOSFETs using EBIC imaging. Applied Physics Letters. 118(20). 1 indexed citations
8.
Xiao, T. Patrick, Christopher H. Bennett, F. B. Mancoff, et al.. (2021). Heavy-Ion-Induced Displacement Damage Effects in Magnetic Tunnel Junctions With Perpendicular Anisotropy. IEEE Transactions on Nuclear Science. 68(5). 581–587. 11 indexed citations
9.
Chang, Liang, Karalee Jarvis, Paul G. Kotula, et al.. (2021). Irradiation Effects on Perpendicular Anisotropy Spin–Orbit Torque Magnetic Tunnel Junctions. IEEE Transactions on Nuclear Science. 68(5). 665–670. 16 indexed citations
10.
Leonard, Thomas M., Can Cui, Xue Lin, et al.. (2021). Spin Orbit Torque Domain Wall-Magnetic Tunnel Junction Devices and Circuits for In-Memory and Neuromorphic Computing. Bulletin of the American Physical Society. 1 indexed citations
11.
Xiao, T. Patrick, et al.. (2021). Analysis and mitigation of parasitic resistance effects for analog in-memory neural network acceleration. Semiconductor Science and Technology. 36(11). 114004–114004. 7 indexed citations
12.
Hu, Xuan, Christopher H. Bennett, Felipe García‐Sánchez, et al.. (2020). Domain Wall Leaky Integrate-and-Fire Neurons with Shape-Based Configurable Activation Functions. arXiv (Cornell University). 15 indexed citations
13.
Xiao, T. Patrick, Christopher H. Bennett, Ben Feinberg, Sapan Agarwal, & Matthew Marinella. (2020). Analog architectures for neural network acceleration based on non-volatile memory. Applied Physics Reviews. 7(3). 137 indexed citations
14.
Bennett, Christopher H., Vivek Parmar, Laurie E. Calvet, et al.. (2019). Contrasting Advantages of Learning With Random Weights and Backpropagation in Non-Volatile Memory Neural Networks. IEEE Access. 7. 73938–73953. 4 indexed citations
15.
Friedman, Joseph S., Xuan Hu, Christopher H. Bennett, et al.. (2019). Shape-Based Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron. IEEE Transactions on Electron Devices. 66(11). 4970–4975. 44 indexed citations
16.
Xiao, T. Patrick, Matthew Marinella, Christopher H. Bennett, et al.. (2019). Energy and Performance Benchmarking of a Domain Wall-Magnetic Tunnel Junction Multibit Adder. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits. 5(2). 188–196. 21 indexed citations
17.
Hu, Xuan, et al.. (2019). Three-terminal magnetic tunnel junction synapse circuits showing spike-timing-dependent plasticity. Journal of Physics D Applied Physics. 52(49). 49LT01–49LT01. 23 indexed citations
18.
Yakopcic, Chris, et al.. (2019). Memristor Model Optimization Based on Parameter Extraction From Device Characterization Data. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 39(5). 1084–1095. 27 indexed citations
19.
Jacobs-Gedrim, Robin, David Russell Hughart, Sapan Agarwal, et al.. (2018). Training a Neural Network on Analog TaO<italic>x</italic> ReRAM Devices Irradiated With Heavy Ions: Effects on Classification Accuracy Demonstrated With CrossSim. IEEE Transactions on Nuclear Science. 66(1). 54–60. 11 indexed citations
20.
Jacobs-Gedrim, Robin, Sapan Agarwal, Ronald S. Goeke, et al.. (2018). Analog high resistance bilayer RRAM device for hardware acceleration of neuromorphic computation. Journal of Applied Physics. 124(20). 14 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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