Sahil Shah
- Finance top 2%
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- Advanced Memory and Neural Computing 15
- Perovskite Materials and Applications 7
- Polymers and Plastics top 5%
- Bioengineering top 5%
- Analytical Chemistry and Sensors 10
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- Analog and Mixed-Signal Circuit Design 22
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- Electrochemical Analysis and Applications 6
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- Neuroscience and Neural Engineering 6
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- EEG and Brain-Computer Interfaces 6
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- Experimental Learning in Engineering 5
- Co-authors
- Priyank ThakkarKetan KotechaJigar PatelJennifer HaslerDieter NeherMartin StolterfohtJonathan WarbyEmilio Gutierrez‐Partida
- Journals
- Nature Communications (2 papers)SHILAP Revista de lepidopterología (1 paper)Advanced Energy Materials (3 papers)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Sahil Shah
67 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Management Science and Operations Research 924
- Finance 299
- Electrical and Electronic Engineering 1.3k
- Polymers and Plastics 309
- Bioengineering 82
Countries citing papers authored by Sahil Shah
This map shows the geographic impact of Sahil Shah'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 Sahil Shah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sahil Shah more than expected).
Fields of papers citing papers by Sahil Shah
This network shows the impact of papers produced by Sahil Shah. 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 Sahil Shah. The network helps show where Sahil Shah may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sahil Shah, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 10 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 3 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 3 | |
| 8 | 2023 | 38 | |
| 9 | 2023 | 33 | |
| 10 | 2023 | 4 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 78 | |
| 13 | 2023 | 2 | |
| 14 | 2023 | 11 | |
| 15 | 2022 | 145 | |
| 16 | Understanding Performance Limiting Interfacial Recombination in pin Perovskite Solar Cellsbreakdown → | 2022 | 201 |
| 17 | 2022 | 121 | |
| 18 | 2021 | 11 | |
| 19 | 2017 | 25 | |
| 20 | Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniquesbreakdown → | 2014 | 691 |
About Sahil Shah
Sahil Shah is a scholar working on Bioengineering, Electrochemistry and Electrical and Electronic Engineering, having authored 72 papers that have together received 2.3k indexed citations. Recurring topics across this work include Analog and Mixed-Signal Circuit Design (22 papers), Advanced Memory and Neural Computing (15 papers), Analytical Chemistry and Sensors (10 papers), Perovskite Materials and Applications (7 papers), Electrochemical Analysis and Applications (6 papers), Neuroscience and Neural Engineering (6 papers), EEG and Brain-Computer Interfaces (6 papers) and Experimental Learning in Engineering (5 papers). The work is most often cited by research in Management Science and Operations Research (924 citations), Finance (299 citations) and Electrical and Electronic Engineering (1.3k citations). Sahil Shah has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Priyank Thakkar, Ketan Kotecha, Jigar Patel, Jigar Patel, Jennifer Hasler, Dieter Neher, Martin Stolterfoht, Jonathan Warby, Emilio Gutierrez‐Partida and Felix Lang. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and Advanced Energy Materials.
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.