Brian Crafton

451 total citations
21 papers, 292 citations indexed

About

Brian Crafton is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Brian Crafton has authored 21 papers receiving a total of 292 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Electrical and Electronic Engineering, 3 papers in Computer Networks and Communications and 3 papers in Artificial Intelligence. Recurrent topics in Brian Crafton's work include Advanced Memory and Neural Computing (17 papers), Ferroelectric and Negative Capacitance Devices (15 papers) and Semiconductor materials and devices (7 papers). Brian Crafton is often cited by papers focused on Advanced Memory and Neural Computing (17 papers), Ferroelectric and Negative Capacitance Devices (15 papers) and Semiconductor materials and devices (7 papers). Brian Crafton collaborates with scholars based in United States, Taiwan and South Korea. Brian Crafton's co-authors include Arijit Raychowdhury, Samuel Spetalnick, Muya Chang, Yu-Der Chih, Meng‐Fan Chang, Win-San Khwa, Aileen Luo, Ashwin Sanjay Lele, Zoran Krivokapić and Suman Datta and has published in prestigious journals such as IEEE Journal of Solid-State Circuits, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems and IEEE Transactions on Circuits and Systems I Regular Papers.

In The Last Decade

Brian Crafton

19 papers receiving 290 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian Crafton United States 11 262 64 36 25 24 21 292
Chung-Cheng Chou Taiwan 7 301 1.1× 48 0.8× 68 1.9× 20 0.8× 19 0.8× 8 326
S. S. Teja Nibhanupudi United States 8 287 1.1× 52 0.8× 52 1.4× 20 0.8× 39 1.6× 16 320
Samuel Spetalnick United States 11 257 1.0× 47 0.7× 24 0.7× 20 0.8× 32 1.3× 21 294
Robert M. Radway United States 10 239 0.9× 31 0.5× 24 0.7× 34 1.4× 22 0.9× 23 288
Peter Deaville United States 6 334 1.3× 96 1.5× 25 0.7× 30 1.2× 22 0.9× 12 366
Wantong Li United States 11 305 1.2× 75 1.2× 43 1.2× 26 1.0× 20 0.8× 33 357
Yun-Chen Lo Taiwan 7 311 1.2× 78 1.2× 47 1.3× 47 1.9× 13 0.5× 18 356
Yasmin Halawani United Arab Emirates 9 268 1.0× 62 1.0× 79 2.2× 17 0.7× 25 1.0× 29 318
Gokul Krishnan United States 10 239 0.9× 60 0.9× 31 0.9× 57 2.3× 13 0.5× 26 280
Tai-Hao Wen Taiwan 8 312 1.2× 74 1.2× 48 1.3× 30 1.2× 15 0.6× 12 343

Countries citing papers authored by Brian Crafton

Since Specialization
Citations

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

Fields of papers citing papers by Brian Crafton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian Crafton

This figure shows the co-authorship network connecting the top 25 collaborators of Brian Crafton. A scholar is included among the top collaborators of Brian Crafton 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 Brian Crafton. Brian Crafton 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.
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.
2.
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.
3.
Crafton, Brian, Samuel Spetalnick, Muya Chang, & Arijit Raychowdhury. (2024). A 28nm Approximate / Binary 6T CAM for Sequence Alignment. 1–2. 1 indexed citations
4.
Spetalnick, Samuel, Ashwin Sanjay Lele, Brian Crafton, et al.. (2024). 30.1 A 40nm VLIW Edge Accelerator with 5MB of 0.256pJ/b RRAM and a Localization Solver for Bristle Robot Surveillance. 482–484. 6 indexed citations
5.
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
6.
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
7.
Sun, Xiaoyu, Weidong Cao, Brian Crafton, et al.. (2023). Efficient Processing of MLPerf Mobile Workloads Using Digital Compute-In-Memory Macros. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 43(4). 1191–1205. 10 indexed citations
8.
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
9.
10.
Lele, Ashwin Sanjay, Muya Chang, Samuel Spetalnick, et al.. (2023). Neuromorphic Swarm on RRAM Compute-in-Memory Processor for Solving QUBO Problem. 1–6. 1 indexed citations
11.
Crafton, Brian, Zishen Wan, Samuel Spetalnick, et al.. (2022). Improving compute in-memory ECC reliability with successive correction. Proceedings of the 59th ACM/IEEE Design Automation Conference. 745–750. 12 indexed citations
12.
Crafton, Brian, et al.. (2022). Characterization and Mitigation of IR-Drop in RRAM-based Compute In-Memory. 2022 IEEE International Symposium on Circuits and Systems (ISCAS). 70–74. 3 indexed citations
13.
Chang, Muya, Samuel Spetalnick, Brian Crafton, et al.. (2022). A 40nm 60.64TOPS/W ECC-Capable Compute-in-Memory/Digital 2.25MB/768KB RRAM/SRAM System with Embedded Cortex M3 Microprocessor for Edge Recommendation Systems. 2022 IEEE International Solid- State Circuits Conference (ISSCC). 1–3. 38 indexed citations
14.
Spetalnick, Samuel, Muya Chang, Brian Crafton, et al.. (2022). A 40nm 64kb 26.56TOPS/W 2.37Mb/mm2RRAM Binary/Compute-in-Memory Macro with 4.23x Improvement in Density and >75% Use of Sensing Dynamic Range. 2022 IEEE International Solid- State Circuits Conference (ISSCC). 1–3. 37 indexed citations
15.
Crafton, Brian, Samuel Spetalnick, Jong‐Hyeok Yoon, & Arijit Raychowdhury. (2021). Statistical Optimization of Compute In-Memory Performance Under Device Variation. 1–6. 4 indexed citations
16.
Crafton, Brian, et al.. (2021). Hardware-Algorithm Co-Design Enabling Efficient Event-based Object Detection. 1–4. 3 indexed citations
17.
Crafton, Brian, et al.. (2020). A Hardware-Friendly Approach Towards Sparse Neural Networks Based on LFSR-Generated Pseudo-Random Sequences. IEEE Transactions on Circuits and Systems I Regular Papers. 68(2). 751–764. 10 indexed citations
18.
Crafton, Brian, Samuel Spetalnick, Yan Fang, & Arijit Raychowdhury. (2020). Merged Logic and Memory Fabrics for Accelerating Machine Learning Workloads. IEEE Design and Test. 38(1). 39–68. 10 indexed citations
19.
Crafton, Brian, et al.. (2019). Local Learning in RRAM Neural Networks with Sparse Direct Feedback Alignment. 1–6. 8 indexed citations
20.
Wang, Zheng, Brian Crafton, Jorge Gómez, et al.. (2018). Experimental Demonstration of Ferroelectric Spiking Neurons for Unsupervised Clustering. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 13.3.1–13.3.4. 70 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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