Sudip Nag

1.3k total citations
55 papers, 983 citations indexed

About

Sudip Nag is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Biomedical Engineering. According to data from OpenAlex, Sudip Nag has authored 55 papers receiving a total of 983 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Electrical and Electronic Engineering, 24 papers in Cellular and Molecular Neuroscience and 24 papers in Biomedical Engineering. Recurrent topics in Sudip Nag's work include Neuroscience and Neural Engineering (24 papers), Gas Sensing Nanomaterials and Sensors (13 papers) and Wireless Power Transfer Systems (11 papers). Sudip Nag is often cited by papers focused on Neuroscience and Neural Engineering (24 papers), Gas Sensing Nanomaterials and Sensors (13 papers) and Wireless Power Transfer Systems (11 papers). Sudip Nag collaborates with scholars based in India, Singapore and United States. Sudip Nag's co-authors include Prasanta Kumar Guha, Snehanjan Acharyya, Nitish V. Thakor, S. B. Majumder, Arpan Pal, Sanjay Kimbahune, Avik Ghose, Goutam Saha, Reza Erfani and Pedram Mohseni and has published in prestigious journals such as Journal of Power Sources, International Journal of Heat and Mass Transfer and Analytica Chimica Acta.

In The Last Decade

Sudip Nag

53 papers receiving 963 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sudip Nag India 18 706 544 255 199 146 55 983
Murat Okandan United States 20 925 1.3× 557 1.0× 70 0.3× 144 0.7× 188 1.3× 101 1.3k
Gul Hassan South Korea 20 918 1.3× 654 1.2× 266 1.0× 148 0.7× 159 1.1× 50 1.2k
Mingu Kang South Korea 15 568 0.8× 581 1.1× 171 0.7× 41 0.2× 102 0.7× 36 885
Keekeun Lee South Korea 23 1.2k 1.7× 1.0k 1.9× 295 1.2× 164 0.8× 366 2.5× 111 1.7k
Vamsy P. Chodavarapu Canada 18 636 0.9× 656 1.2× 259 1.0× 179 0.9× 97 0.7× 100 1.3k
Kee Scholten United States 16 369 0.5× 424 0.8× 81 0.3× 360 1.8× 39 0.3× 33 800
Chunwei Zhang China 16 891 1.3× 455 0.8× 142 0.6× 228 1.1× 207 1.4× 36 1.1k
Tianda Fu United States 11 752 1.1× 688 1.3× 64 0.3× 226 1.1× 142 1.0× 13 1.4k
Tsung‐Hsien Lin Taiwan 22 1.2k 1.8× 733 1.3× 60 0.2× 80 0.4× 125 0.9× 120 1.7k
Young Geun Song South Korea 20 1.0k 1.5× 493 0.9× 422 1.7× 68 0.3× 490 3.4× 38 1.2k

Countries citing papers authored by Sudip Nag

Since Specialization
Citations

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

Fields of papers citing papers by Sudip Nag

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sudip Nag

This figure shows the co-authorship network connecting the top 25 collaborators of Sudip Nag. A scholar is included among the top collaborators of Sudip Nag 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 Sudip Nag. Sudip Nag 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.
Nag, Sudip, et al.. (2025). Energy-Efficient Adaptive Neural Stimulator With Waveform Prediction by Sub-Threshold Interrogation of the Electrode-Tissue Interface. IEEE Transactions on Biomedical Circuits and Systems. 19(6). 1142–1159.
2.
Acharyya, Snehanjan, et al.. (2023). Smart and Selective Gas Sensor System Empowered With Machine Learning Over IoT Platform. IEEE Internet of Things Journal. 11(3). 4218–4226. 28 indexed citations
3.
Xu, Jianxiong, Sudip Nag, Gerard O’Leary, et al.. (2023). Fascicle-Selective Ultrasound-Powered Bidirectional Wireless Peripheral Nerve Interface IC. IEEE Transactions on Biomedical Circuits and Systems. 17(6). 1237–1256. 11 indexed citations
4.
Nag, Sudip, et al.. (2023). Nucleic acid based point-of-care diagnostic technology for infectious disease detection using machine learning empowered smartphone-interfaced quantitative colorimetry. International Journal of Biological Macromolecules. 253(Pt 5). 127137–127137. 6 indexed citations
5.
Acharyya, Snehanjan, Sudip Nag, & Prasanta Kumar Guha. (2022). Ultra-selective tin oxide-based chemiresistive gas sensor employing signal transform and machine learning techniques. Analytica Chimica Acta. 1217. 339996–339996. 49 indexed citations
6.
Acharyya, Snehanjan, Sudip Nag, Sanjay Kimbahune, et al.. (2021). Selective Discrimination of VOCs Applying Gas Sensing Kinetic Analysis over a Metal Oxide-Based Chemiresistive Gas Sensor. ACS Sensors. 6(6). 2218–2224. 139 indexed citations
7.
Nag, Sudip, et al.. (2021). Performance of fire protective coatings on structural steel member exposed to high temperature. Journal of Structural Fire Engineering. 5 indexed citations
8.
Acharyya, Snehanjan, Sudip Nag, & Prasanta Kumar Guha. (2020). Selective Detection of VOCs With WO3 Nanoplates-Based Single Chemiresistive Sensor Device Using Machine Learning Algorithms. IEEE Sensors Journal. 21(5). 5771–5778. 40 indexed citations
9.
Acharyya, Snehanjan, et al.. (2020). Single resistive sensor for selective detection of multiple VOCs employing SnO2 hollowspheres and machine learning algorithm: A proof of concept. Sensors and Actuators B Chemical. 321. 128484–128484. 101 indexed citations
10.
Nag, Sudip, et al.. (2018). Capacitive Wireless Power and Data Transfer for Implantable Medical Devices. 1–4. 24 indexed citations
11.
Blasiak, Agata, Sudip Nag, & In Hong Yang. (2018). Subcellular Optogenetic Stimulation Platform for Studying Activity-Dependent Axon Myelination In Vitro. Methods in molecular biology. 1791. 207–224. 2 indexed citations
12.
Bhattacharyya, Tarun Kanti, et al.. (2018). A Smart Temperature Sensor and Controller for Bioelectronic Implants. 1–4. 1 indexed citations
13.
14.
Nag, Sudip & Nitish V. Thakor. (2016). Implantable neurotechnologies: electrical stimulation and applications. Medical & Biological Engineering & Computing. 54(1). 63–76. 34 indexed citations
15.
16.
Nag, Sudip, Dinesh Sharma, & Nitish V. Thakor. (2013). A 24 V<inf>pp</inf> compliant biphasic stimulator for inductively powered animal behavior studies. PubMed. 2013. 3242–3245. 5 indexed citations
17.
Nag, Sudip, Xiaofeng Jia, Nitish V. Thakor, & Dinesh Sharma. (2012). Flexible Charge Balanced Stimulator With 5.6 fC Accuracy for 140 nC Injections. IEEE Transactions on Biomedical Circuits and Systems. 7(3). 266–275. 30 indexed citations
18.
Nag, Sudip, et al.. (2011). Wirelessly powered stimulator and recorder for neuronal interfaces. PubMed. 2011. 5612–5616. 2 indexed citations
19.
Nag, Sudip, et al.. (2009). An ultra-sensitive &#8710;R/R measurement system for biochemical sensors using piezoresistive micro-cantilevers. PubMed. 2009. 3794–3797. 11 indexed citations
20.
Nag, Sudip, et al.. (2008). Fabrication and Characterization of a Polymeric Microcantilever With an Encapsulated Hotwire CVD Polysilicon Piezoresistor. Journal of Microelectromechanical Systems. 18(1). 79–87. 42 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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