Shantanu Chakrabartty
- Biomedical Engineering top 5%
- Analog and Mixed-Signal Circuit Design 31
- Advanced Sensor and Energy Harvesting Materials 19
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- Structural Health Monitoring Techniques 21
- Bioengineering top 5%
- Signal Processing top 5%
- Speech and Audio Processing 20
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- Advanced Memory and Neural Computing 23
- Energy Harvesting in Wireless Networks 18
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- Innovative Energy Harvesting Technologies 29
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- Advanced biosensing and bioanalysis techniques 21
- Co-authors
- Gert CauwenberghsNizar LajnefKenji AonoEvangelyn C. AlociljaRigoberto BurgueñoChuan WangJunyi ZhaoYong Wang
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Shantanu Chakrabartty
192 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 131
- Biomedical Engineering 948
- Civil and Structural Engineering 364
- Bioengineering 91
- Signal Processing 168
- Electrical and Electronic Engineering 892
Countries citing papers authored by Shantanu Chakrabartty
This map shows the geographic impact of Shantanu Chakrabartty'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 Shantanu Chakrabartty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shantanu Chakrabartty more than expected).
Fields of papers citing papers by Shantanu Chakrabartty
This network shows the impact of papers produced by Shantanu Chakrabartty. 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 Shantanu Chakrabartty. The network helps show where Shantanu Chakrabartty may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shantanu Chakrabartty, 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 | 3 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 11 | |
| 6 | 2023 | 0 | |
| 7 | 2023 | 1 | |
| 8 | 2021 | 1 | |
| 9 | 2020 | 21 | |
| 10 | 2020 | 13 | |
| 11 | 2019 | 2 | |
| 12 | 2017 | 6 | |
| 13 | 2012 | 12 | |
| 14 | 2010 | 5 | |
| 15 | 2009 | 6 | |
| 16 | Gini Support Vector Machine: Quadratic Entropy Based Robust Multi-Class Probability Regression | 2007 | 15 |
| 17 | 2006 | 1 | |
| 18 | 2005 | 28 | |
| 19 | Sub-Microwatt Analog VLSI Support Vector Machine for Pattern Classification and Sequence Estimation | 2004 | 21 |
| 20 | Forward-decoding kernel-based phone sequence recognition | 2002 | 2 |
About Shantanu Chakrabartty
Shantanu Chakrabartty is a scholar working on Signal Processing, Biomedical Engineering and Computational Mathematics, having authored 201 papers that have together received 2.2k indexed citations. Recurring topics across this work include Analog and Mixed-Signal Circuit Design (31 papers), Innovative Energy Harvesting Technologies (29 papers), Advanced Memory and Neural Computing (23 papers), Advanced biosensing and bioanalysis techniques (21 papers), Structural Health Monitoring Techniques (21 papers), Speech and Audio Processing (20 papers), Advanced Sensor and Energy Harvesting Materials (19 papers) and Energy Harvesting in Wireless Networks (18 papers). The work is most often cited by research in Biomedical Engineering (948 citations), Civil and Structural Engineering (364 citations) and Bioengineering (91 citations). Shantanu Chakrabartty has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Gert Cauwenberghs, Nizar Lajnef, Kenji Aono, Evangelyn C. Alocilja, Rigoberto Burgueño, Chuan Wang, Junyi Zhao, Yong Wang, Liang Zhou and Hadi Salehi. Their work appears in journals such as Nature Communications, ACS Nano and Nature Nanotechnology.
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.