Suma Cardwell

697 total citations
25 papers, 120 citations indexed

About

Suma Cardwell is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Suma Cardwell has authored 25 papers receiving a total of 120 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Electrical and Electronic Engineering, 12 papers in Artificial Intelligence and 4 papers in Cognitive Neuroscience. Recurrent topics in Suma Cardwell's work include Advanced Memory and Neural Computing (22 papers), Ferroelectric and Negative Capacitance Devices (14 papers) and Neural Networks and Reservoir Computing (6 papers). Suma Cardwell is often cited by papers focused on Advanced Memory and Neural Computing (22 papers), Ferroelectric and Negative Capacitance Devices (14 papers) and Neural Networks and Reservoir Computing (6 papers). Suma Cardwell collaborates with scholars based in United States. Suma Cardwell's co-authors include J. Darby Smith, James B. Aimone, Catherine D. Schuman, Jean Anne C. Incorvia, Frances S. Chance, Conrad D. James, Shashank Misra, L. C. Bland, Andrew D. Kent and Shashank Misra and has published in prestigious journals such as Advanced Materials, Nanotechnology and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

In The Last Decade

Suma Cardwell

18 papers receiving 118 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Suma Cardwell United States 5 88 56 28 16 14 25 120
L. C. Bland United States 3 40 0.5× 33 0.6× 19 0.7× 6 0.4× 7 0.5× 7 77
Peter Deaville United States 6 334 3.8× 96 1.7× 15 0.5× 12 0.8× 14 1.0× 12 366
Abhairaj Singh Netherlands 10 177 2.0× 31 0.6× 15 0.5× 4 0.3× 14 1.0× 16 196
Juan P. Brito Spain 10 39 0.4× 102 1.8× 49 1.8× 14 0.9× 15 1.1× 31 213
Po-Wei Chiu United States 8 215 2.4× 155 2.8× 16 0.6× 23 1.4× 10 0.7× 19 294
Todor Mladenov United States 10 189 2.1× 71 1.3× 76 2.7× 19 1.2× 11 0.8× 22 269
Navid Anjum Aadit United States 10 179 2.0× 221 3.9× 64 2.3× 54 3.4× 9 0.6× 12 354
Nestan Tsiskaridze United States 9 193 2.2× 96 1.7× 20 0.7× 41 2.6× 3 0.2× 10 303
Timothée Leleu Japan 8 130 1.5× 330 5.9× 70 2.5× 26 1.6× 14 1.0× 16 387
Ameya D. Patil United States 6 233 2.6× 69 1.2× 9 0.3× 7 0.4× 4 0.3× 12 265

Countries citing papers authored by Suma Cardwell

Since Specialization
Citations

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

Fields of papers citing papers by Suma Cardwell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suma Cardwell

This figure shows the co-authorship network connecting the top 25 collaborators of Suma Cardwell. A scholar is included among the top collaborators of Suma Cardwell 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 Suma Cardwell. Suma Cardwell 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.
Cardwell, Suma, J. Darby Smith, Samuel Liu, et al.. (2025). AI-Guided Codesign for Novel Computing Paradigms. 849–856.
2.
Boyle, James, et al.. (2025). SANA-FE: Simulating Advanced Neuromorphic Architectures for Fast Exploration. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 44(8). 3165–3178. 1 indexed citations
3.
4.
Liu, Samuel, J. Darby Smith, James B. Aimone, et al.. (2024). Magnetic tunnel junction random number generators applied to dynamically tuned probability trees driven by spin orbit torque. Nanotechnology. 35(27). 275204–275204. 5 indexed citations
5.
Cardwell, Suma, et al.. (2024). Neural-Inspired Dendritic Multiplication Using a Reconfigurable Analog Integrated Circuit. 1–5. 1 indexed citations
6.
Cardwell, Suma, et al.. (2024). Bio-Inspired Active Silicon Dendrite for Direction Selectivity. 343–349.
7.
Cardwell, Suma, et al.. (2024). Device Codesign using Reinforcement Learning. 1–5. 3 indexed citations
8.
Misra, Shashank, et al.. (2024). (Invited) There’s More to a Probabilistic Neuromorphic Computing System Than Noisy Devices. ECS Meeting Abstracts. MA2024-01(57). 3019–3019. 1 indexed citations
9.
Boyle, James, et al.. (2023). Performance and Energy Simulation of Spiking Neuromorphic Architectures for Fast Exploration. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1–4. 4 indexed citations
10.
Severa, William, et al.. (2023). Neuromorphic Population Evaluation using the Fugu Framework. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1–7.
11.
Misra, Shashank, L. C. Bland, Suma Cardwell, et al.. (2023). Probabilistic Neural Computing with Stochastic Devices (Adv. Mater. 37/2023). Advanced Materials. 35(37). 4 indexed citations
12.
Chance, Frances S. & Suma Cardwell. (2023). Shunting Inhibition as a Neural-Inspired Mechanism for Multiplication in Neuromorphic Architectures. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 41–46. 4 indexed citations
13.
Cardwell, Suma & Frances S. Chance. (2023). Dendritic Computation for Neuromorphic Applications. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1–5. 5 indexed citations
14.
Misra, Shashank, L. C. Bland, Suma Cardwell, et al.. (2022). Probabilistic Neural Computing with Stochastic Devices. Advanced Materials. 35(37). e2204569–e2204569. 55 indexed citations
15.
Liu, Samuel, Suma Cardwell, Catherine D. Schuman, et al.. (2022). Random Bitstream Generation Using Voltage-Controlled Magnetic Anisotropy and Spin Orbit Torque Magnetic Tunnel Junctions. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits. 8(2). 194–202. 16 indexed citations
16.
Cardwell, Suma, Catherine D. Schuman, J. Darby Smith, et al.. (2022). Probabilistic Neural Circuits leveraging AI-Enhanced Codesign for Random Number Generation.. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
17.
Chance, Frances S., et al.. (2022). Benchmarking a Bio-inspired SNN on a Neuromorphic System. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 63–66. 6 indexed citations
18.
Vineyard, Craig M., Suma Cardwell, Frances S. Chance, et al.. (2022). Neural Mini-Apps as a Tool for Neuromorphic Computing Insight. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 40–49. 3 indexed citations
19.
Cardwell, Suma. (2021). Achieving Extreme Heterogeneity: CoDesign using Neuromorphic Processors.. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
20.
Bennett, Christopher H., T. Patrick Xiao, Ben Feinberg, et al.. (2020). Evaluating complexity and resilience trade-offs in emerging memory inference machines. 1–4. 1 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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2026