Shashi Phoha

1.7k total citations · 1 hit paper
103 papers, 1.2k citations indexed

About

Shashi Phoha is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computational Theory and Mathematics. According to data from OpenAlex, Shashi Phoha has authored 103 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Artificial Intelligence, 38 papers in Computer Networks and Communications and 25 papers in Computational Theory and Mathematics. Recurrent topics in Shashi Phoha's work include Target Tracking and Data Fusion in Sensor Networks (17 papers), Petri Nets in System Modeling (17 papers) and Energy Efficient Wireless Sensor Networks (16 papers). Shashi Phoha is often cited by papers focused on Target Tracking and Data Fusion in Sensor Networks (17 papers), Petri Nets in System Modeling (17 papers) and Energy Efficient Wireless Sensor Networks (16 papers). Shashi Phoha collaborates with scholars based in United States, India and United Kingdom. Shashi Phoha's co-authors include Asok Ray, Christian Gobert, Edward W. Reutzel, Abdalla R. Nassar, Jan Petrich, Pradipta Biswas, Kushal Mukherjee, Shalabh Gupta, Richard R. Brooks and Vir V. Phoha and has published in prestigious journals such as Automatica, IEEE Transactions on Neural Networks and Learning Systems and Neural Networks.

In The Last Decade

Shashi Phoha

92 papers receiving 1.1k citations

Hit Papers

Application of supervised machine learning for defect det... 2018 2026 2020 2023 2018 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Application of supervised machine learning for defect detection during metallic powder bed fusion additive manufacturing using high resolution imaging.
    2018 348 citations Shashi Phoha et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shashi Phoha United States 18 351 336 248 232 164 103 1.2k
Ying Zheng China 22 193 0.5× 311 0.9× 173 0.7× 158 0.7× 150 0.9× 127 1.5k
Mark Schwabacher United States 15 283 0.8× 179 0.5× 77 0.3× 787 3.4× 86 0.5× 45 1.8k
Qidan Zhu China 24 355 1.0× 189 0.6× 124 0.5× 227 1.0× 78 0.5× 201 2.0k
Yupu Yang China 22 358 1.0× 307 0.9× 54 0.2× 656 2.8× 74 0.5× 97 1.9k
Yu Guo China 28 131 0.4× 1.3k 3.8× 242 1.0× 208 0.9× 91 0.6× 144 2.7k
Jun Wu China 23 277 0.8× 122 0.4× 96 0.4× 302 1.3× 33 0.2× 151 1.5k
Liang Chen China 21 150 0.4× 788 2.3× 57 0.2× 426 1.8× 115 0.7× 130 2.3k
Zheng Sun China 18 117 0.3× 215 0.6× 112 0.5× 141 0.6× 186 1.1× 70 1.2k
Wojciech Paszke Poland 25 289 0.8× 425 1.3× 40 0.2× 293 1.3× 79 0.5× 120 2.3k
A. Alessandri Italy 30 321 0.9× 115 0.3× 112 0.5× 543 2.3× 162 1.0× 175 2.9k

Countries citing papers authored by Shashi Phoha

Since Specialization
Citations

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

Fields of papers citing papers by Shashi Phoha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shashi Phoha

This figure shows the co-authorship network connecting the top 25 collaborators of Shashi Phoha. A scholar is included among the top collaborators of Shashi Phoha 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 Shashi Phoha. Shashi Phoha 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.
Saab, Khaled, et al.. (2022). A multivariate adaptive gradient algorithm with reduced tuning efforts. Neural Networks. 152. 499–509. 23 indexed citations
2.
Phoha, Shashi, et al.. (2022). An adaptive polyak heavy-ball method. Machine Learning. 111(9). 3245–3277. 15 indexed citations
3.
Phoha, Shashi, et al.. (2018). Learning From Multiple Imperfect Instructors in Sensor Networks. IEEE Transactions on Neural Networks and Learning Systems. 29(10). 5166–5172. 1 indexed citations
4.
Phoha, Shashi, et al.. (2015). Learning context-aware measurement models. 4491–4496. 1 indexed citations
5.
Sarkar, Soumalya, Kin Gwn Lore, Soumik Sarkar, et al.. (2015). Early Detection of Combustion Instability from Hi-speed Flame Images via Deep Learning and Symbolic Time Series Analysis. Annual Conference of the PHM Society. 7(1). 22 indexed citations
6.
Ray, Asok, et al.. (2014). Performance robustness of feature extraction for target detection & classification. 3814–3819. 3 indexed citations
7.
Bein, Doina, et al.. (2013). Dynamic data-driven sensor network adaptation for border control. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8711. 87110J–87110J. 5 indexed citations
8.
Madan, Bharat B., et al.. (2010). Modeling and simulation of failure tolerance in scale free networks. Winter Simulation Conference. 2907–2914. 1 indexed citations
9.
Bein, Doina, Wolfgang Bein, & Shashi Phoha. (2010). Efficient Data Centers, Cloud Computing in the Future of Distributed Computing. 70–75. 7 indexed citations
10.
Rao, C. R., Kushal Mukherjee, Shalabh Gupta, Asok Ray, & Shashi Phoha. (2009). Underwater mine detection using symbolic pattern analysis of sidescan sonar images. 5416–5421. 20 indexed citations
11.
12.
Phoha, Shashi, et al.. (2007). C3L: an integrated computation, communication and control language for dynamically controlled heterogeneous devices. 79–85. 2 indexed citations
13.
Carl, Glenn, Shashi Phoha, George Kesidis, & Bharat B. Madan. (2006). Path preserving scale down for validation of internet inter-domain routing protocols. Winter Simulation Conference. 2210–2218. 3 indexed citations
14.
Madan, Bharat B., Shashi Phoha, & Kishor S. Trivedi. (2005). StackOFFence: a technique for defending against buffer overflow attacks. 56. 656–661 Vol. 1. 12 indexed citations
15.
Biswas, Pratik K. & Shashi Phoha. (2005). A Middleware-Driven Architecture for Information Dissemination in Distributed Sensor Networks. 605–610. 18 indexed citations
16.
Cao, Guohong, Guiling Wang, Thomas La Porta, Shashi Phoha, & Wensheng Zhang. (2005). Distributed Algorithms for Deploying Mobile Sensors.. 427–440. 3 indexed citations
17.
Eberbach, Eugene & Shashi Phoha. (2003). SAMON: communication, cooperation and learning of mobile autonomous robotic agents. 229–236. 4 indexed citations
18.
Ray, Asok & Shashi Phoha. (2000). Calibration and estimation of redundant signals. Automatica. 36(10). 1525–1534. 6 indexed citations
19.
Zhang, Hui, Asok Ray, & Shashi Phoha. (2000). Hybrid life-extending control of mechanical systems: experimental validation of the concept. Automatica. 36(1). 23–36. 23 indexed citations
20.
Ray, Asok & Shashi Phoha. (1988). Service access procedure (SAP) for a transport layer protocol. Telematics and Informatics. 5(1). 65–73. 1 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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