Sayeh Sharify

740 total citations
10 papers, 262 citations indexed

About

Sayeh Sharify is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Sayeh Sharify has authored 10 papers receiving a total of 262 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 7 papers in Electrical and Electronic Engineering and 5 papers in Artificial Intelligence. Recurrent topics in Sayeh Sharify's work include Advanced Neural Network Applications (8 papers), Adversarial Robustness in Machine Learning (5 papers) and CCD and CMOS Imaging Sensors (4 papers). Sayeh Sharify is often cited by papers focused on Advanced Neural Network Applications (8 papers), Adversarial Robustness in Machine Learning (5 papers) and CCD and CMOS Imaging Sensors (4 papers). Sayeh Sharify collaborates with scholars based in Canada and United Kingdom. Sayeh Sharify's co-authors include Alberto Delmás Lascorz, Andreas Moshovos, Kevin Siu, Patrick Judd, Mostafa Mahmoud, Zissis Poulos, Jorge Albericio, Tayler Hetherington, Tor M. Aamodt and Natalie Enright Jerger and has published in prestigious journals such as Computer and IEEE Micro.

In The Last Decade

Sayeh Sharify

10 papers receiving 259 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sayeh Sharify Canada	5	187	143	116	56	24	10	262
Alberto Delmás Lascorz Canada	6	193 1.0×	145 1.0×	118 1.0×	62 1.1×	27 1.1×	12	273
Kevin Siu Canada	8	251 1.3×	191 1.3×	142 1.2×	67 1.2×	31 1.3×	10	356
Igor Đurđanović United States	4	163 0.9×	144 1.0×	104 0.9×	58 1.0×	12 0.5×	5	262
Zhuoran Song China	8	105 0.6×	91 0.6×	70 0.6×	25 0.4×	19 0.8×	48	220
Jiecao Yu United States	6	250 1.3×	163 1.1×	183 1.6×	88 1.6×	52 2.2×	7	365
Linyan Mei Belgium	9	122 0.7×	187 1.3×	66 0.6×	83 1.5×	53 2.2×	17	300
David J. Palframan United States	6	223 1.2×	188 1.3×	169 1.5×	133 2.4×	83 3.5×	10	380
Yaohui Cai United States	4	162 0.9×	37 0.3×	117 1.0×	21 0.4×	17 0.7×	5	235
Sheng-Chun Kao United States	8	100 0.5×	125 0.9×	68 0.6×	118 2.1×	76 3.2×	15	265
Coleman Hooper United States	6	52 0.3×	92 0.6×	92 0.8×	46 0.8×	41 1.7×	11	215

Countries citing papers authored by Sayeh Sharify

Since Specialization

Citations

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

Fields of papers citing papers by Sayeh Sharify

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sayeh Sharify

This figure shows the co-authorship network connecting the top 25 collaborators of Sayeh Sharify. A scholar is included among the top collaborators of Sayeh Sharify 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 Sayeh Sharify. Sayeh Sharify 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:

10 of 10 papers shown

1.

Sharify, Sayeh, Miloš Nikolić, Mostafa Mahmoud, et al.. (2021). Boveda: Building an On-Chip Deep Learning Memory Hierarchy Brick by Brick. 3. 1–20. 3 indexed citations

2.

Lascorz, Alberto Delmás, Patrick Judd, Zissis Poulos, et al.. (2019). Bit-Tactical. 749–763. 68 indexed citations

3.

Lascorz, Alberto Delmás, Sayeh Sharify, Patrick Judd, et al.. (2019). ShapeShifter. 28–41. 21 indexed citations

4.

Sharify, Sayeh, Alberto Delmás Lascorz, Mostafa Mahmoud, et al.. (2019). Laconic deep learning inference acceleration. 304–317. 52 indexed citations

5.

Mahmoud, Mostafa, Zissis Poulos, Alberto Delmás Lascorz, et al.. (2019). Accelerating Image-Sensor-Based Deep Learning Applications. IEEE Micro. 39(5). 26–35. 1 indexed citations

6.

Sharify, Sayeh, Alberto Delmás Lascorz, Kevin Siu, Patrick Judd, & Andreas Moshovos. (2018). Loom: Exploiting Weight and Activation Precisions to Accelerate Convolutional Neural Networks. 1–6. 67 indexed citations

7.

Sharify, Sayeh, Alberto Delmás Lascorz, Kevin Siu, Patrick Judd, & Andreas Moshovos. (2018). Loom. 1–6. 44 indexed citations

8.

Moshovos, Andreas, Jorge Albericio, Patrick Judd, et al.. (2018). Identifying and Exploiting Ineffectual Computations to Enable Hardware Acceleration of Deep Learning. abs 1706 504. 356–360. 2 indexed citations

9.

Moshovos, Andreas, Jorge Albericio, Patrick Judd, et al.. (2018). Exploiting Typical Values to Accelerate Deep Learning. Computer. 51(5). 18–30. 1 indexed citations

10.

Moshovos, Andreas, Jorge Albericio, Patrick Judd, et al.. (2018). Value-Based Deep-Learning Acceleration. IEEE Micro. 38(1). 41–55. 3 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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