Maryam Parsa

1.6k total citations · 1 hit paper
42 papers, 971 citations indexed

About

Maryam Parsa is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Maryam Parsa has authored 42 papers receiving a total of 971 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Electrical and Electronic Engineering, 15 papers in Artificial Intelligence and 12 papers in Cognitive Neuroscience. Recurrent topics in Maryam Parsa's work include Advanced Memory and Neural Computing (28 papers), Ferroelectric and Negative Capacitance Devices (19 papers) and Neural dynamics and brain function (12 papers). Maryam Parsa is often cited by papers focused on Advanced Memory and Neural Computing (28 papers), Ferroelectric and Negative Capacitance Devices (19 papers) and Neural dynamics and brain function (12 papers). Maryam Parsa collaborates with scholars based in United States, Spain and United Kingdom. Maryam Parsa's co-authors include Catherine D. Schuman, J. Parker Mitchell, Shruti Kulkarni, Prasanna Date, Bill Kay, Kaushik Roy, Abhronil Sengupta, Bing Han, Robert M. Patton and Thomas E. Potok and has published in prestigious journals such as Nature Communications, Optics Express and IEEE Transactions on Electron Devices.

In The Last Decade

Maryam Parsa

35 papers receiving 943 citations

Hit Papers

Opportunities for neuromorphic computing algorithms and a... 2022 2026 2023 2024 2022 200 400 600
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. Opportunities for neuromorphic computing algorithms and applications
    2022 615 citations Catherine D. Schuman, Shruti Kulkarni et al. Nature Computational Science profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maryam Parsa United States 11 761 365 206 186 91 42 971
Prasanna Date United States 12 712 0.9× 475 1.3× 173 0.8× 181 1.0× 48 0.5× 36 966
Shruti Kulkarni United States 11 755 1.0× 376 1.0× 242 1.2× 206 1.1× 46 0.5× 41 954
Weier Wan United States 9 877 1.2× 204 0.6× 110 0.5× 229 1.2× 106 1.2× 16 947
Morteza Hosseini United States 10 446 0.6× 223 0.6× 170 0.8× 144 0.8× 50 0.5× 19 607
J. Parker Mitchell United States 13 801 1.1× 408 1.1× 256 1.2× 189 1.0× 41 0.5× 31 981
S. G. Hu China 15 779 1.0× 206 0.6× 219 1.1× 363 2.0× 70 0.8× 34 890
Arnab Neelim Mazumder United States 8 441 0.6× 207 0.6× 127 0.6× 132 0.7× 50 0.5× 19 578
Chetan Singh Thakur India 16 592 0.8× 166 0.5× 165 0.8× 124 0.7× 192 2.1× 76 855
Massimo Giordano United States 8 911 1.2× 237 0.6× 125 0.6× 251 1.3× 116 1.3× 11 959

Countries citing papers authored by Maryam Parsa

Since Specialization
Citations

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

Fields of papers citing papers by Maryam Parsa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maryam Parsa

This figure shows the co-authorship network connecting the top 25 collaborators of Maryam Parsa. A scholar is included among the top collaborators of Maryam Parsa 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 Maryam Parsa. Maryam Parsa 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.
2.
Alouani, Ihsen, et al.. (2025). Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study. Proceedings on Privacy Enhancing Technologies. 2025(2). 243–257. 1 indexed citations
3.
Alouani, Ihsen, et al.. (2024). BrainLeaks: On the Privacy-Preserving Properties of Neuromorphic Architectures against Model Inversion Attacks. SPIRE - Sciences Po Institutional REpository. 705–712. 1 indexed citations
4.
Parsa, Maryam, et al.. (2024). The Laterality of Port Catheter Placement in Breast Cancer Patients: Investigating the Impact of Side Selection. Indian Journal of Surgical Oncology. 16(1). 344–348.
5.
Risbud, Sumedh R., et al.. (2024). Asynchronous Neuromorphic Optimization in Lava. 776–778.
6.
Zhu, Kevin, Connor Mattson, Ricardo de la Vega Marcos, et al.. (2024). Spiking Neural Networks as a Controller for Emergent Swarm Agents. 319–326.
7.
Schwartz, Gregory G., et al.. (2024). Hardware-Algorithm Re-Engineering of Retinal Circuit for Intelligent Object Motion Segmentation. 256–263. 1 indexed citations
8.
Alouani, Ihsen, et al.. (2024). Watermarking Neuromorphic Brains: Intellectual Property Protection in Spiking Neural Networks. SPIRE - Sciences Po Institutional REpository. 287–294. 1 indexed citations
9.
Zhu, Kevin, et al.. (2023). Zespol: A Lightweight Environment for Training Swarming Agents. 1–5. 1 indexed citations
10.
Kulkarni, Shruti, et al.. (2023). Hyperparameter Optimization and Feature Inclusion in Graph Neural Networks for Spiking Implementation. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1541–1546. 2 indexed citations
11.
Parsa, Maryam, et al.. (2023). IRIS: Integrated Retinal Functionality in Image Sensors. Frontiers in Neuroscience. 17. 1241691–1241691. 5 indexed citations
12.
Aimone, James B., Prasanna Date, G. A. Fonseca Guerra, et al.. (2022). A review of non-cognitive applications for neuromorphic computing. Neuromorphic Computing and Engineering. 2(3). 32003–32003. 33 indexed citations
13.
Schuman, Catherine D., Shruti Kulkarni, Maryam Parsa, et al.. (2022). Opportunities for neuromorphic computing algorithms and applications. Nature Computational Science. 2(1). 10–19. 615 indexed citations breakdown →
14.
Schuman, Catherine D., James S. Plank, Garrett S. Rose, & Maryam Parsa. (2022). Lessons Learned in Omnidirectional Co-Design of Neuromorphic Systems. 16. 1–5. 1 indexed citations
15.
Parsa, Maryam, et al.. (2021). Multi-Objective Hyperparameter Optimization for Spiking Neural Network Neuroevolution. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1225–1232. 2 indexed citations
16.
Patton, Robert M., Catherine D. Schuman, Shruti Kulkarni, et al.. (2021). Neuromorphic Computing for Autonomous Racing. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1–5. 19 indexed citations
17.
Ziabari, Amirkoushyar, Maryam Parsa, Yi Xuan, et al.. (2020). Far-field thermal imaging below diffraction limit. Optics Express. 28(5). 7036–7036. 9 indexed citations
18.
Parsa, Maryam, J. Parker Mitchell, Catherine D. Schuman, et al.. (2019). Bayesian-based Hyperparameter Optimization for Spiking Neuromorphic Systems. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 4472–4478. 14 indexed citations
19.
Ziabari, Amirkoushyar, Pol Torres, Bjorn Vermeersch, et al.. (2018). Full-field thermal imaging of quasiballistic crosstalk reduction in nanoscale devices. Nature Communications. 9(1). 255–255. 61 indexed citations
20.
Sengupta, Abhronil, Maryam Parsa, Bing Han, & Kaushik Roy. (2016). Probabilistic Deep Spiking Neural Systems Enabled by Magnetic Tunnel Junction. IEEE Transactions on Electron Devices. 63(7). 2963–2970. 75 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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