Geoffrey W. Burr

15.2k total citations · 7 hit papers
162 papers, 10.7k citations indexed

About

Geoffrey W. Burr is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Geoffrey W. Burr has authored 162 papers receiving a total of 10.7k indexed citations (citations by other indexed papers that have themselves been cited), including 135 papers in Electrical and Electronic Engineering, 58 papers in Materials Chemistry and 57 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Geoffrey W. Burr's work include Advanced Memory and Neural Computing (72 papers), Ferroelectric and Negative Capacitance Devices (56 papers) and Photorefractive and Nonlinear Optics (45 papers). Geoffrey W. Burr is often cited by papers focused on Advanced Memory and Neural Computing (72 papers), Ferroelectric and Negative Capacitance Devices (56 papers) and Photorefractive and Nonlinear Optics (45 papers). Geoffrey W. Burr collaborates with scholars based in United States, Switzerland and France. Geoffrey W. Burr's co-authors include R. M. Shelby, Pritish Narayanan, B. N. Kurdi, Rohit S. Shenoy, Hyunsang Hwang, Kumar Virwani, Severin Sidler, Irem Boybat, C. Lam and Demetri Psaltis and has published in prestigious journals such as Nature, Science and Nature Communications.

In The Last Decade

Geoffrey W. Burr

158 papers receiving 10.4k citations

Hit Papers

5 papers align trajectories

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.

Resistive switching materials for information processing

2020 905 citations Geoffrey W. Burr et al. profile →
Neuromorphic computing using non-volatile memory

2016 818 citations Geoffrey W. Burr, R. M. Shelby et al. profile →
Phase-change random access memory: A scalable technology

2008 791 citations Simone Raoux, Geoffrey W. Burr et al. profile →
Equivalent-accuracy accelerated neural-network training using analogue memory

2018 770 citations Stefano Ambrogio, Pritish Narayanan et al. profile →
Experimental Demonstration and Tolerancing of a Large-Scale Neural Network (165 000 Synapses) Using Phase-Change Memory as the Synaptic Weight Element

2015 741 citations Geoffrey W. Burr, R. M. Shelby et al. profile →
Overview of candidate device technologies for storage-class memory

2008 529 citations Geoffrey W. Burr, B. N. Kurdi et al. profile →
Holographic data storage technology

2000 526 citations Geoffrey W. Burr, H. Coufal et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Geoffrey W. Burr United States	43	9.0k	2.9k	2.3k	1.8k	1.4k	162	10.7k
Abu Sebastian Switzerland	46	10.3k 1.1×	3.1k 1.1×	2.0k 0.9×	2.2k 1.2×	2.9k 2.0×	224	12.7k
Jianshi Tang China	54	8.9k 1.0×	3.7k 1.3×	3.5k 1.5×	2.4k 1.3×	2.0k 1.4×	217	13.2k
R. M. Shelby United States	52	8.6k 1.0×	2.9k 1.0×	5.2k 2.2×	1.0k 0.6×	1.8k 1.3×	149	13.0k
Massimiliano Di Ventra United States	58	10.9k 1.2×	3.2k 1.1×	5.0k 2.1×	2.2k 1.3×	1.2k 0.8×	267	15.5k
Julie Grollier France	42	5.9k 0.7×	2.0k 0.7×	5.2k 2.2×	815 0.5×	1.8k 1.3×	131	9.8k
Suman Datta United States	68	15.6k 1.7×	5.5k 1.9×	1.8k 0.8×	492 0.3×	1.1k 0.8×	514	18.1k
Sergey Savel’ev United Kingdom	38	3.5k 0.4×	757 0.3×	2.8k 1.2×	1.4k 0.8×	688 0.5×	201	7.4k
Evangelos Eleftheriou Switzerland	48	9.7k 1.1×	2.0k 0.7×	791 0.3×	1.5k 0.9×	2.1k 1.5×	189	11.7k
Ru Huang China	49	9.5k 1.1×	1.7k 0.6×	415 0.2×	2.3k 1.3×	1.3k 0.9×	637	10.6k
Hyunsang Hwang South Korea	57	13.4k 1.5×	3.8k 1.3×	604 0.3×	4.0k 2.2×	1.2k 0.8×	424	14.3k

Countries citing papers authored by Geoffrey W. Burr

Since Specialization

Citations

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

Fields of papers citing papers by Geoffrey W. Burr

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Geoffrey W. Burr. 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 Geoffrey W. Burr. The network helps show where Geoffrey W. Burr may publish in the future.

Co-authorship network of co-authors of Geoffrey W. Burr

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

All Works

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20 of 20 papers shown

Ambrogio, Stefano, Pritish Narayanan, Charles Mackin, et al.. (2025). Demonstration of transformer-based ALBERT model on a 14nm analog AI inference chip. Nature Communications. 16(1). 8661–8661. 1 indexed citations

Simon, William, Irem Boybat, Gagandeep Singh, et al.. (2025). CiMBA: Accelerating Genome Sequencing Through On-Device Basecalling via Compute-in-Memory. IEEE Transactions on Parallel and Distributed Systems. 36(6). 1130–1145. 1 indexed citations

Chen, An, Stefano Ambrogio, Pritish Narayanan, et al.. (2024). (Invited) Emerging Nonvolatile Memories for Analog Neuromorphic Computing. ECS Meeting Abstracts. MA2024-01(21). 1293–1293. 1 indexed citations

Li, Ning, Charles Mackin, An Chen, et al.. (2023). Optimization of Projected Phase Change Memory for Analog In‐Memory Computing Inference. Advanced Electronic Materials. 9(6). 5 indexed citations

Chan, V., Wei‐Tsu Tseng, Kang Min Ok, et al.. (2023). Yield Methodology and Heater Process Variation in Phase Change Memory (PCM) Technology for Analog Computing. IEEE Transactions on Semiconductor Manufacturing. 36(3). 327–331. 1 indexed citations

Rasch, Malte J., Charles Mackin, Manuel Le Gallo, et al.. (2023). Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators. Nature Communications. 14(1). 5282–5282. 77 indexed citations

Mackin, Charles, Malte J. Rasch, An Chen, et al.. (2022). Optimised weight programming for analogue memory-based deep neural networks. Nature Communications. 13(1). 3765–3765. 34 indexed citations

Jain, Shubham, Hsinyu Tsai, R. Muralidhar, et al.. (2022). A Heterogeneous and Programmable Compute-In-Memory Accelerator Architecture for Analog-AI Using Dense 2-D Mesh. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 31(1). 114–127. 28 indexed citations

Mackin, Charles, Pritish Narayanan, Stefano Ambrogio, et al.. (2020). Neuromorphic Computing with Phase Change, Device Reliability, and Variability Challenges. 1–10. 4 indexed citations

10.

Kim, Sang‐Bum, Geoffrey W. Burr, Wanki Kim, & Sung‐Wook Nam. (2019). Phase-change memory cycling endurance. MRS Bulletin. 44(9). 710–714. 52 indexed citations

11.

Mackin, Charles, et al.. (2019). Accelerating Deep Neural Networks with Analog Memory Devices. Bulletin of the American Physical Society. 2019. 1 indexed citations

12.

Sanz‐Paz, María, Geoffrey W. Burr, N.F. van Hulst, et al.. (2018). Enhancing Magnetic Light Emission with All-Dielectric Optical Nanoantennas. Nano Letters. 18(6). 3481–3487. 63 indexed citations

13.

Burr, Geoffrey W., M. BrightSky, Abu Sebastian, et al.. (2016). Recent Progress in Phase-ChangeMemory Technology. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 6(2). 146–162. 280 indexed citations

14.

Boybat, Irem, Severin Sidler, Carmelo di Nolfo, et al.. (2015). PCM for Neuromorphic Applications: Impact of Device Characteristics on Neural Network Performance. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1 indexed citations

15.

Burr, Geoffrey W., Kumar Virwani, Rohit S. Shenoy, et al.. (2013). Recovery dynamics and fast (sub-50ns) read operation with Access Devices for 3D crosspoint memory based on mixed-ionic-electronic-conduction (MIEC). Symposium on VLSI Technology. 18 indexed citations

16.

Grosjean, Thierry, Mathieu Mivelle, & Geoffrey W. Burr. (2010). Polarization-dependent extraction properties of bare fiber probes. Optics Letters. 35(3). 357–357. 6 indexed citations

17.

Krebs, Daniel, Simone Raoux, Charles Rettner, et al.. (2009). Characterization of phase change memory materials using phase change bridge devices. Journal of Applied Physics. 106(5). 25 indexed citations

18.

Coufal, H., et al.. (2004). Accuracy and scalability in holographic content-addressable storage. Conference on Lasers and Electro-Optics. 1. 2 indexed citations

19.

Burr, Geoffrey W., et al.. (2001). High-Density and High-Capacity Holographic Data Storage. 2 indexed citations

20.

Burr, Geoffrey W. & Fai Mok. (1994). Storage of 10,000 holograms in LiNbO 3 :Fe. Conference on Lasers and Electro-Optics. 10 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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