Hossein Valavi

1.4k total citations · 1 hit paper
10 papers, 992 citations indexed

About

Hossein Valavi is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hossein Valavi has authored 10 papers receiving a total of 992 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Electrical and Electronic Engineering, 4 papers in Artificial Intelligence and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hossein Valavi's work include Advanced Memory and Neural Computing (7 papers), Ferroelectric and Negative Capacitance Devices (5 papers) and Neural Networks and Applications (2 papers). Hossein Valavi is often cited by papers focused on Advanced Memory and Neural Computing (7 papers), Ferroelectric and Negative Capacitance Devices (5 papers) and Neural Networks and Applications (2 papers). Hossein Valavi collaborates with scholars based in United States. Hossein Valavi's co-authors include Naveen Verma, Yinqi Tang, Hongyang Jia, Peter J. Ramadge, Eric J. Nestler, Bonan Zhang, Peter Deaville, Jintao Zhang, Rakshit Pathak and Jinseok Lee and has published in prestigious journals such as IEEE Journal of Solid-State Circuits, IEEE Solid-State Circuits Magazine and International Conference on Artificial Intelligence and Statistics.

In The Last Decade

Hossein Valavi

9 papers receiving 975 citations

Hit Papers

In-Memory Computing: Advances and Prospects 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hossein Valavi United States 7 892 216 161 147 75 10 992
Yinqi Tang United States 9 614 0.7× 195 0.9× 118 0.7× 112 0.8× 71 0.9× 12 732
Hongyang Jia China 11 668 0.7× 218 1.0× 157 1.0× 99 0.7× 91 1.2× 36 826
Sujan K. Gonugondla United States 13 640 0.7× 165 0.8× 140 0.9× 103 0.7× 72 1.0× 25 737
Xin Si China 17 1.3k 1.4× 239 1.1× 272 1.7× 206 1.4× 103 1.4× 52 1.4k
Je-Min Hung Taiwan 12 744 0.8× 138 0.6× 123 0.8× 71 0.5× 53 0.7× 15 815
En-Yu Yang United States 8 494 0.6× 151 0.7× 91 0.6× 131 0.9× 58 0.8× 15 620
Amogh Agrawal United States 15 673 0.8× 136 0.6× 132 0.8× 53 0.4× 60 0.8× 32 774
Tsung-Yung Jonathan Chang Taiwan 20 1.2k 1.3× 196 0.9× 276 1.7× 123 0.8× 126 1.7× 48 1.4k
Yen-Cheng Chiu Taiwan 14 1.0k 1.1× 167 0.8× 172 1.1× 97 0.7× 52 0.7× 20 1.1k
Hung-Jen Liao Taiwan 16 1.3k 1.5× 137 0.6× 345 2.1× 99 0.7× 125 1.7× 40 1.4k

Countries citing papers authored by Hossein Valavi

Since Specialization
Citations

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

Fields of papers citing papers by Hossein Valavi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hossein Valavi

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

All Works

10 of 10 papers shown
1.
Jia, Hongyang, Yinqi Tang, Hossein Valavi, et al.. (2021). 15.1 A Programmable Neural-Network Inference Accelerator Based on Scalable In-Memory Computing. 236–238. 117 indexed citations
2.
Lee, Jinseok, Hossein Valavi, Yinqi Tang, & Naveen Verma. (2021). Fully Row/Column-Parallel In-memory Computing SRAM Macro employing Capacitor-based Mixed-signal Computation with 5-b Inputs. 1–2. 58 indexed citations
3.
Jia, Hongyang, Yinqi Tang, Hossein Valavi, et al.. (2021). Scalable and Programmable Neural Network Inference Accelerator Based on In-Memory Computing. IEEE Journal of Solid-State Circuits. 57(1). 198–211. 61 indexed citations
4.
Valavi, Hossein, et al.. (2020). Revisiting the Landscape of Matrix Factorization.. International Conference on Artificial Intelligence and Statistics. 1629–1638.
5.
Jia, Hongyang, Hossein Valavi, Yinqi Tang, Jintao Zhang, & Naveen Verma. (2020). A Programmable Heterogeneous Microprocessor Based on Bit-Scalable In-Memory Computing. IEEE Journal of Solid-State Circuits. 55(9). 2609–2621. 154 indexed citations
6.
Valavi, Hossein, Peter J. Ramadge, Eric J. Nestler, & Naveen Verma. (2019). A 64-Tile 2.4-Mb In-Memory-Computing CNN Accelerator Employing Charge-Domain Compute. IEEE Journal of Solid-State Circuits. 54(6). 1789–1799. 213 indexed citations
7.
Jia, Hongyang, et al.. (2019). A Programmable Embedded Microprocessor for Bit-scalable In-memory Computing. 1–29. 6 indexed citations
8.
Verma, Naveen, Hongyang Jia, Hossein Valavi, et al.. (2019). In-Memory Computing: Advances and Prospects. IEEE Solid-State Circuits Magazine. 11(3). 43–55. 269 indexed citations breakdown →
9.
Valavi, Hossein, Peter J. Ramadge, Eric J. Nestler, & Naveen Verma. (2018). A Mixed-Signal Binarized Convolutional-Neural-Network Accelerator Integrating Dense Weight Storage and Multiplication for Reduced Data Movement. 141–142. 113 indexed citations
10.
Valavi, Hossein & Peter J. Ramadge. (2018). An Upper-Bound on the Required Size of a Neural Network Classifier. 3. 2356–2360. 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026