Ashwin Sanjay Lele

435 total citations
28 papers, 210 citations indexed

About

Ashwin Sanjay Lele is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Ashwin Sanjay Lele has authored 28 papers receiving a total of 210 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Electrical and Electronic Engineering, 7 papers in Cognitive Neuroscience and 6 papers in Cellular and Molecular Neuroscience. Recurrent topics in Ashwin Sanjay Lele's work include Advanced Memory and Neural Computing (23 papers), Ferroelectric and Negative Capacitance Devices (7 papers) and Neural dynamics and brain function (5 papers). Ashwin Sanjay Lele is often cited by papers focused on Advanced Memory and Neural Computing (23 papers), Ferroelectric and Negative Capacitance Devices (7 papers) and Neural dynamics and brain function (5 papers). Ashwin Sanjay Lele collaborates with scholars based in United States, Taiwan and India. Ashwin Sanjay Lele's co-authors include Arijit Raychowdhury, Yan Fang, Haicheng Wu, Gregory Diamos, Muya Chang, Yu-Der Chih, Samuel Spetalnick, Brian Crafton, Jin Wang and Win-San Khwa and has published in prestigious journals such as Nano Letters, IEEE Journal of Solid-State Circuits and IEEE Electron Device Letters.

In The Last Decade

Ashwin Sanjay Lele

24 papers receiving 207 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ashwin Sanjay Lele United States 9 117 49 44 35 34 28 210
Manuel Eggimann Switzerland 10 148 1.3× 37 0.8× 23 0.5× 40 1.1× 50 1.5× 16 273
Slim Ben Saoud Tunisia 10 81 0.7× 45 0.9× 87 2.0× 114 3.3× 37 1.1× 49 292
Xiaoyang Zeng China 10 122 1.0× 78 1.6× 50 1.1× 42 1.2× 73 2.1× 77 300
Ali Jahanian Iran 9 220 1.9× 35 0.7× 34 0.8× 107 3.1× 39 1.1× 78 327
Matthieu Arzel France 8 165 1.4× 69 1.4× 77 1.8× 17 0.5× 22 0.6× 33 230
Beatrice Bussolino Italy 5 129 1.1× 96 2.0× 34 0.8× 39 1.1× 96 2.8× 6 270
Yi Kang China 9 221 1.9× 75 1.5× 30 0.7× 55 1.6× 41 1.2× 65 308
Syed Kamran Haider China 9 104 0.9× 80 1.6× 88 2.0× 52 1.5× 27 0.8× 29 248
Xiaoyang Zeng China 11 300 2.6× 41 0.8× 41 0.9× 67 1.9× 30 0.9× 71 394

Countries citing papers authored by Ashwin Sanjay Lele

Since Specialization
Citations

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

Fields of papers citing papers by Ashwin Sanjay Lele

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ashwin Sanjay Lele. 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 Ashwin Sanjay Lele. The network helps show where Ashwin Sanjay Lele may publish in the future.

Co-authorship network of co-authors of Ashwin Sanjay Lele

This figure shows the co-authorship network connecting the top 25 collaborators of Ashwin Sanjay Lele. A scholar is included among the top collaborators of Ashwin Sanjay Lele 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 Ashwin Sanjay Lele. Ashwin Sanjay Lele 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.
Wu, Ping-Chun, Win-San Khwa, Ashwin Sanjay Lele, et al.. (2025). A Microscaling Multi-Mode Gain-Cell Computing-in-Memory Macro for Advanced AI Edge Device. IEEE Journal of Solid-State Circuits. 61(1). 211–224.
2.
Khwa, Win-San, Ping-Chun Wu, Jian-Wei Su, et al.. (2025). 14.2 A 16nm 216kb, 188.4TOPS/W and 133.5TFLOPS/W Microscaling Multi-Mode Gain-Cell CIM Macro Edge-AI Devices. 1–3. 1 indexed citations
3.
Crafton, Brian, Xiaochen Peng, Xiaoyu Sun, et al.. (2025). Finding the Pareto Frontier of Low-Precision Data Formats and MAC Architecture for LLM Inference. 1–7.
4.
Lele, Ashwin Sanjay, et al.. (2025). Assessing Design Space for the Device-Circuit Codesign of Nonvolatile Memory-Based Compute-in-Memory Accelerators. Nano Letters. 25(4). 1243–1249. 1 indexed citations
5.
Jhang, Chuan-Jia, Win-San Khwa, Ping-Chun Wu, et al.. (2024). A 22 nm 10.03-237.99 TOPS/W Time-Digital-Hybrid SRAM Compute-in-Memory AI Accelerator for GNN Edge Device Applications. 1(1). 15–25. 1 indexed citations
6.
Spetalnick, Samuel, Ashwin Sanjay Lele, Brian Crafton, et al.. (2024). An Edge Accelerator With 5 MB of 0.256-pJ/bit Embedded RRAM and a Localization Solver for Bristle Robot Surveillance. IEEE Journal of Solid-State Circuits. 60(1). 35–48.
7.
Chang, Muya, Ashwin Sanjay Lele, Samuel Spetalnick, et al.. (2023). A 73.53TOPS/W 14.74TOPS Heterogeneous RRAM In-Memory and SRAM Near-Memory SoC for Hybrid Frame and Event-Based Target Tracking. 426–428. 32 indexed citations
8.
Lele, Ashwin Sanjay, Muya Chang, Samuel Spetalnick, et al.. (2023). A Heterogeneous RRAM In-Memory and SRAM Near-Memory SoC for Fused Frame and Event-Based Target Identification and Tracking. IEEE Journal of Solid-State Circuits. 59(1). 52–64. 13 indexed citations
9.
Spetalnick, Samuel, Muya Chang, S. KONNO, et al.. (2023). A 40-nm Compute-in-Memory Macro With RRAM Addressing IR Drop and Off-State Current. IEEE Solid-State Circuits Letters. 7. 10–13. 4 indexed citations
10.
11.
Lele, Ashwin Sanjay, et al.. (2022). Bio-mimetic high-speed target localization with fused frame and event vision for edge application. Frontiers in Neuroscience. 16. 1010302–1010302. 6 indexed citations
12.
Fang, Yan & Ashwin Sanjay Lele. (2022). Solving Quadratic Unconstrained Binary Optimization with Collaborative Spiking Neural Networks. 84–88. 2 indexed citations
13.
Ting, Albert C.W., et al.. (2022). A Comparison of CNNs and LSTMs for EEG Signal Classification. 23–26.
14.
Lele, Ashwin Sanjay, et al.. (2021). An End-to-End Spiking Neural Network Platform for Edge Robotics: From Event-Cameras to Central Pattern Generation. IEEE Transactions on Cognitive and Developmental Systems. 14(3). 1092–1103. 24 indexed citations
15.
Lele, Ashwin Sanjay, et al.. (2020). Learning to Walk: Bio-Mimetic Hexapod Locomotion via Reinforcement-Based Spiking Central Pattern Generation. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 10(4). 536–545. 14 indexed citations
16.
Lele, Ashwin Sanjay, et al.. (2020). Online Reward-Based Training of Spiking Central Pattern Generator for Hexapod Locomotion. 24. 208–209. 1 indexed citations
17.
Lele, Ashwin Sanjay, et al.. (2017). A simple PECVD SiO<inf>2</inf> OTP memory based PUF for 180nm node for IoT. 1–2. 2 indexed citations
18.
Lele, Ashwin Sanjay, et al.. (2017). Melodic shape stylization for robust and efficient motif detection in Hindustani vocal music. 4. 1–6. 5 indexed citations
19.
Diamos, Gregory, Haicheng Wu, Jin Wang, Ashwin Sanjay Lele, & Sudhakar Yalamanchili. (2013). Relational algorithms for multi-bulk-synchronous processors. 301–302. 18 indexed citations
20.
Diamos, Gregory, Haicheng Wu, Ashwin Sanjay Lele, & Jin Wang. (2012). Efficient Relational Algebra Algorithms and Data Structures for GPU. SMARTech Repository (Georgia Institute of Technology). 27 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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