Mohammad H. Tahersima

1.4k total citations
33 papers, 815 citations indexed

About

Mohammad H. Tahersima is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Mohammad H. Tahersima has authored 33 papers receiving a total of 815 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Electrical and Electronic Engineering, 11 papers in Artificial Intelligence and 10 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Mohammad H. Tahersima's work include Photonic and Optical Devices (18 papers), Neural Networks and Reservoir Computing (10 papers) and Photonic Crystals and Applications (8 papers). Mohammad H. Tahersima is often cited by papers focused on Photonic and Optical Devices (18 papers), Neural Networks and Reservoir Computing (10 papers) and Photonic Crystals and Applications (8 papers). Mohammad H. Tahersima collaborates with scholars based in United States, Japan and Iran. Mohammad H. Tahersima's co-authors include Volker J. Sorger, Devesh K. Jha, Kieran Parsons, Toshiaki Koike‐Akino, Keisuke Kojima, Zhizhen Ma, Chung-Wei Lin, Bingnan Wang, Rubab Amin and Hamed Dalir and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Optics Express.

In The Last Decade

Mohammad H. Tahersima

31 papers receiving 781 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad H. Tahersima United States 12 605 305 246 224 113 33 815
Yibiao Yang China 16 612 1.0× 453 1.5× 242 1.0× 94 0.4× 141 1.2× 77 1.0k
John Peurifoy United States 5 323 0.5× 241 0.8× 214 0.9× 184 0.8× 60 0.5× 5 755
Xiao Hu China 18 839 1.4× 610 2.0× 255 1.0× 81 0.4× 50 0.4× 60 1.1k
Achiya Nagler Israel 3 250 0.4× 150 0.5× 202 0.8× 93 0.4× 71 0.6× 4 581
Uri Arieli Israel 6 249 0.4× 161 0.5× 221 0.9× 94 0.4× 55 0.5× 14 622
Han Du United Kingdom 14 489 0.8× 273 0.9× 93 0.4× 148 0.7× 122 1.1× 52 650
Lakshmi Raju United States 9 212 0.4× 137 0.4× 133 0.5× 106 0.5× 37 0.3× 12 503
Samarth Bhargava United States 4 348 0.6× 289 0.9× 141 0.6× 77 0.3× 19 0.2× 9 553
Victor Grigoriev Cyprus 12 200 0.3× 232 0.8× 152 0.6× 79 0.4× 21 0.2× 25 490
Yuangang Lu China 18 750 1.2× 567 1.9× 217 0.9× 36 0.2× 215 1.9× 128 1.1k

Countries citing papers authored by Mohammad H. Tahersima

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad H. Tahersima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammad H. Tahersima. 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 Mohammad H. Tahersima. The network helps show where Mohammad H. Tahersima may publish in the future.

Co-authorship network of co-authors of Mohammad H. Tahersima

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

All Works

20 of 20 papers shown
1.
Wenny, Brian N., et al.. (2024). Assessment of Spatial Characterization Metrics for On-Orbit Performance of Landsat 8 and 9 Thermal Infrared Sensors. Remote Sensing. 16(19). 3588–3588. 1 indexed citations
2.
Tahersima, Mohammad H., et al.. (2023). Intercomparison of Landsat OLI and JPSS VIIRS Using a Combination of RadCalNet Sites as a Common Reference. Remote Sensing. 15(23). 5562–5562. 1 indexed citations
3.
Thome, Kurtis J., et al.. (2023). Combining RadCalNet Sites for Radiometric Cross Calibration of Landsat 9 and Landsat 8 Operational Land Imagers (OLIs). Remote Sensing. 15(24). 5752–5752. 5 indexed citations
4.
Tahersima, Mohammad H., et al.. (2023). Radiance-based and reflectance-based retrievals of surface reflectance for vicarious calibration. UA Campus Repository (The University of Arizona). 9607. 40–40.
5.
Kojima, Keisuke, Mohammad H. Tahersima, Toshiaki Koike‐Akino, et al.. (2021). Deep Neural Networks for Inverse Design of Nanophotonic Devices. Journal of Lightwave Technology. 39(4). 1010–1019. 37 indexed citations
6.
Kojima, Keisuke, Toshiaki Koike‐Akino, Ye Wang, et al.. (2021). Application of deep learning for nanophotonic device design. 28–28. 2 indexed citations
7.
Kojima, Keisuke, Mohammad H. Tahersima, Toshiaki Koike‐Akino, et al.. (2020). Deep Neural Networks for Designing Integrated Photonics. Th1A.6–Th1A.6. 2 indexed citations
8.
Kojima, Keisuke, Toshiaki Koike‐Akino, Ye Wang, et al.. (2020). Inverse Design of Nanophotonic Devices using Deep Neural Networks. Su1A.1–Su1A.1. 2 indexed citations
9.
Tahersima, Mohammad H., Zhizhen Ma, Yaliang Gui, et al.. (2019). Coupling-enhanced dual ITO layer electro-absorption modulator in silicon photonics. SHILAP Revista de lepidopterología. 42 indexed citations
10.
Amin, Rubab, Rishi Maiti, Zhizhen Ma, et al.. (2019). ITO Mach-Zehnder Modulator on Si. Conference on Lasers and Electro-Optics. JTh2A.45–JTh2A.45. 1 indexed citations
11.
Tahersima, Mohammad H., Keisuke Kojima, Toshiaki Koike‐Akino, et al.. (2019). Nanostructured Photonic Power Splitter Design via Convolutional Neural Networks. Conference on Lasers and Electro-Optics. 1–2. 3 indexed citations
12.
Gui, Yaliang, Mario Miscuglio, Zhizhen Ma, et al.. (2019). Towards integrated metatronics: a holistic approach on precise optical and electrical properties of Indium Tin Oxide. Scientific Reports. 9(1). 11279–11279. 46 indexed citations
13.
Tahersima, Mohammad H., Keisuke Kojima, Toshiaki Koike‐Akino, et al.. (2019). Deep Neural Network Inverse Design of Integrated Photonic Power Splitters. Scientific Reports. 9(1). 1368–1368. 278 indexed citations
14.
Tahersima, Mohammad H., Keisuke Kojima, Toshiaki Koike‐Akino, et al.. (2019). Deep Neural Network Inverse Modeling for Integrated Photonics. W3B.5–W3B.5. 3 indexed citations
15.
Tahersima, Mohammad H., Keisuke Kojima, Toshiaki Koike‐Akino, et al.. (2019). Nanostructured Photonic Power Splitter Design via Convolutional Neural Networks. Conference on Lasers and Electro-Optics. SW4J.6–SW4J.6. 3 indexed citations
16.
Tahersima, Mohammad H. & Volker J. Sorger. (2016). Strong Photon Absorption in 2-D Material-Based Spiral Photovoltaic Cells. MRS Advances. 1(59). 3915–3921. 2 indexed citations
17.
Tahersima, Mohammad H. & Volker J. Sorger. (2015). Enhanced photon absorption in spiral nanostructured solar cells using layered 2D materials. Nanotechnology. 26(34). 344005–344005. 31 indexed citations
18.
Tahersima, Mohammad H., et al.. (2013). Design of stable model reference adaptive system via Lyapunov rule for control of a chemical reactor. 348–353. 8 indexed citations
19.
20.
Tahersima, Mohammad H., et al.. (2011). Forecasting Stock Exchange Movements Using Neural Networks: A Case Study. 30. 123–126. 11 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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