Sangheon Oh

672 total citations
27 papers, 485 citations indexed

About

Sangheon Oh is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Sangheon Oh has authored 27 papers receiving a total of 485 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Electrical and Electronic Engineering, 12 papers in Artificial Intelligence and 4 papers in Signal Processing. Recurrent topics in Sangheon Oh's work include Advanced Memory and Neural Computing (18 papers), Ferroelectric and Negative Capacitance Devices (11 papers) and Neural Networks and Reservoir Computing (7 papers). Sangheon Oh is often cited by papers focused on Advanced Memory and Neural Computing (18 papers), Ferroelectric and Negative Capacitance Devices (11 papers) and Neural Networks and Reservoir Computing (7 papers). Sangheon Oh collaborates with scholars based in United States, South Korea and Spain. Sangheon Oh's co-authors include Yuhan Shi, Duygu Kuzum, Xin Liu, Iván K. Schuller, John R. Jameson, Foroozan Koushan, Pavel Salev, Javier del Valle, Yoav Kalcheim and Yi‐Chen Lu and has published in prestigious journals such as Advanced Materials, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Sangheon Oh

23 papers receiving 476 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sangheon Oh United States	10	441	161	108	85	84	27	485
Jian Kang China	16	493 1.1×	148 0.9×	58 0.5×	85 1.0×	58 0.7×	52	635
Nathan McDonald United States	14	782 1.8×	385 2.4×	149 1.4×	128 1.5×	41 0.5×	35	867
Guanrui Wang China	9	446 1.0×	135 0.8×	153 1.4×	131 1.5×	33 0.4×	17	554
Rashmi Jha United States	14	689 1.6×	169 1.0×	58 0.5×	57 0.7×	78 0.9×	93	772
Massimo Giordano United States	8	911 2.1×	251 1.6×	237 2.2×	125 1.5×	87 1.0×	11	959
Chih-Cheng Chang Taiwan	9	297 0.7×	120 0.7×	61 0.6×	22 0.3×	49 0.6×	21	381
Alexander H. Hsia United States	7	419 1.0×	117 0.7×	107 1.0×	38 0.4×	57 0.7×	11	460
Sijie Ma Hong Kong	9	570 1.3×	179 1.1×	141 1.3×	62 0.7×	95 1.1×	12	654
Xiaohua Xu China	7	518 1.2×	199 1.2×	53 0.5×	77 0.9×	102 1.2×	18	656
Jong Hoon Shin South Korea	9	782 1.8×	214 1.3×	417 3.9×	263 3.1×	66 0.8×	16	879

Countries citing papers authored by Sangheon Oh

Since Specialization

Citations

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

Fields of papers citing papers by Sangheon Oh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sangheon Oh

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Brown, Timothy D., Sangheon Oh, Christopher Perez, et al.. (2025). An electro-optical Mott neuron based on niobium dioxide. Nature Electronics. 8(8). 672–679. 2 indexed citations

Oh, Sangheon, T. Patrick Xiao, Christopher R. Bennett, et al.. (2024). Understanding and Manipulating Electronic Noise in Electrochemical Random Access Memory for Neuromorphic Computing. 1–2.

Oh, Sangheon, Timothy D. Brown, Fatme Jardali, et al.. (2024). Selective modulation of electronic transport in VO2 induced by 10 keV helium ion irradiation. Journal of Applied Physics. 135(12). 2 indexed citations

Woo, Kyung Seok, N. Ghenzi, A. Alec Talin, et al.. (2024). Memristors with Tunable Volatility for Reconfigurable Neuromorphic Computing. ACS Nano. 18(26). 17007–17017. 27 indexed citations

Woo, Kyung Seok, N. Ghenzi, A. Alec Talin, et al.. (2024). Graphlet Decomposition Using Random-Walk Memristors. 1–4.

Kumar, Ashwani, Sangheon Oh, Jeong Hun Kim, et al.. (2024). Multi-level, forming and filament free, bulk switching trilayer RRAM for neuromorphic computing at the edge. Nature Communications. 15(1). 3492–3492. 54 indexed citations

Oh, Sangheon, Byoung Ki Choi, Eli Rotenberg, et al.. (2024). Tuning the Spin Transition and Carrier Type in Rare‐Earth Cobaltates via Compositional Complexity (Adv. Mater. 47/2024). Advanced Materials. 36(47).

Oh, Sangheon, Byoung Ki Choi, Eli Rotenberg, et al.. (2024). Tuning the Spin Transition and Carrier Type in Rare‐Earth Cobaltates via Compositional Complexity. Advanced Materials. 36(47). e2406885–e2406885. 2 indexed citations

Oh, Sangheon, T. Patrick Xiao, Christopher H. Bennett, et al.. (2023). Bayesian Neural Network Implemented by Dynamically Programmable Noise in Vanadium Oxide. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1 indexed citations

10.

Shi, Yuhan, Sangheon Oh, Javier del Valle, et al.. (2023). Integration of Ag-CBRAM crossbars and Mott ReLU neurons for efficient implementation of deep neural networks in hardware. SHILAP Revista de lepidopterología. 3(3). 34007–34007. 3 indexed citations

11.

Shi, Yuhan, et al.. (2023). A Versatile and Efficient Neuromorphic Platform for Compute-in-Memory with Selector-less Memristive Crossbars. 1–4. 2 indexed citations

12.

Oh, Sangheon, Yuhan Shi, Javier del Valle, et al.. (2021). Energy-efficient Mott activation neuron for full-hardware implementation of neural networks. Nature Nanotechnology. 16(6). 680–687. 115 indexed citations

13.

Shi, Yuhan, et al.. (2021). A Neuromorphic Brain Interface Based on RRAM Crossbar Arrays for High Throughput Real-Time Spike Sorting. IEEE Transactions on Electron Devices. 69(4). 2137–2144. 13 indexed citations

14.

Shi, Yuhan, et al.. (2021). High Throughput Neuromorphic Brain Interface with CuO_x Resistive Crossbars for Real-time Spike Sorting. 2021 IEEE International Electron Devices Meeting (IEDM). 16.5.1–16.5.4. 8 indexed citations

15.

Kuzum, Duygu, Yuhan Shi, & Sangheon Oh. (2020). (Invited) Device-Algorithm Codesign for Efficient Neuro-inspired Computing with Resistive Memory Devices. ECS Meeting Abstracts. MA2020-02(31). 2038–2038. 1 indexed citations

16.

Shi, Yuhan, et al.. (2019). A Soft-Pruning Method Applied During Training of Spiking Neural Networks for In-memory Computing Applications. Frontiers in Neuroscience. 13. 405–405. 28 indexed citations

17.

Shi, Yuhan, Sangheon Oh, Xin Liu, et al.. (2018). Neuroinspired unsupervised learning and pruning with subquantum CBRAM arrays. Nature Communications. 9(1). 5312–5312. 88 indexed citations

18.

Oh, Sangheon, Yuhan Shi, Xin Liu, Jungwoo Song, & Duygu Kuzum. (2018). Drift-Enhanced Unsupervised Learning of Handwritten Digits in Spiking Neural Network With PCM Synapses. IEEE Electron Device Letters. 39(11). 1768–1771. 37 indexed citations

19.

Oh, Sangheon & Kyu-Sik Park. (2016). Optimal Acoustic Sound Localization System Based on a Tetrahedron-Shaped Microphone Array. Journal of KIISE. 43(1). 13–26. 1 indexed citations

20.

Park, Kyu-Sik, et al.. (2005). MRTB framework: a robust content-based music retrieval and browsing. IEEE Transactions on Consumer Electronics. 51(1). 117–122. 7 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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