Farshid Ashtiani

16 papers receiving 516 citations

Hit Papers

An on-chip photonic deep neural network for image classification 2022 · 397 citations
3970+1+2Years since publication100200300

Peers

Farshid Ashtiani
Comparison fields: 5 of 49
  • Acoustics and Ultrasonics 17
  • Artificial Intelligence 362
  • Electrical and Electronic Engineering 470
  • Instrumentation 14
  • Atomic and Molecular Physics, and Optics 114
Replace Lingxiao Wan with:
Lingxiao Wan Singapore
Alexander J. Geers United States
Bohan Li United States
Wenchan Dong China
Tingzhao Fu China
Ying Zuo China
Yujun Zhao China
Zebin Huang China
Shi-Yuan Ma United States
Farshid Ashtiani relative to Lingxiao Wan Singapore Lingxiao Wan's profile →
Citations per field
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Citations per year

Countries citing papers authored by Farshid Ashtiani

Since Specialization
Citations

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

Fields of papers citing papers by Farshid Ashtiani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Farshid Ashtiani, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Farshid Ashtiani Line = papers co-authored together Farshid Ashtiani links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1
An on-chip photonic deep neural network for image classification
Hit paper breakdown →
2022397
2 201961
3 202441
4 202425
5 201714
6 20188
7 20195
8 20232
9 20182
10 20252
11 20232
12 20231
13 20241
14 20241
15 20241
16 20211
17 20211
18 20201
19 20250
20 20230

About Farshid Ashtiani

Farshid Ashtiani is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Atomic and Molecular Physics, and Optics, Biomedical Engineering and Instrumentation, having authored 23 papers that have together received 566 indexed citations. Recurring topics across this work include Photonic and Optical Devices (19 papers), Neural Networks and Reservoir Computing (12 papers), Optical Network Technologies (9 papers), Advanced Fiber Laser Technologies (6 papers), Advanced Photonic Communication Systems (5 papers), Optical Coherence Tomography Applications (2 papers), Photonic Crystals and Applications (2 papers) and Topological Materials and Phenomena (2 papers). The work is most often cited by research in Acoustics and Ultrasonics (17 citations), Artificial Intelligence (362 citations), Electrical and Electronic Engineering (470 citations), Instrumentation (14 citations) and Atomic and Molecular Physics, and Optics (114 citations). Farshid Ashtiani has collaborated with scholars based in United States, Canada and Finland. Frequent co-authors include Firooz Aflatouni, Alexander J. Geers, Vahid Nikkhah, Brian Edwards, Nader Engheta, Daniel Pérez, Andrea Blanco‐Redondo, S. J. Ben Yoo, Brian Stern and Jinhie Skarda. Their work appears in journals such as Optics Express, ACS Photonics, Nature Communications, IEEE Transactions on Microwave Theory and Techniques and Nature Photonics.

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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