Krishna Krishnan

520 total citations
21 papers, 327 citations indexed

About

Krishna Krishnan is a scholar working on Industrial and Manufacturing Engineering, Control and Systems Engineering and Management Information Systems. According to data from OpenAlex, Krishna Krishnan has authored 21 papers receiving a total of 327 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Industrial and Manufacturing Engineering, 7 papers in Control and Systems Engineering and 3 papers in Management Information Systems. Recurrent topics in Krishna Krishnan's work include Advanced Manufacturing and Logistics Optimization (3 papers), Vehicle Routing Optimization Methods (3 papers) and Scheduling and Optimization Algorithms (3 papers). Krishna Krishnan is often cited by papers focused on Advanced Manufacturing and Logistics Optimization (3 papers), Vehicle Routing Optimization Methods (3 papers) and Scheduling and Optimization Algorithms (3 papers). Krishna Krishnan collaborates with scholars based in United States and Saudi Arabia. Krishna Krishnan's co-authors include Hongsheng He, Enkhsaikhan Boldsaikhan, Saideep Nannapaneni, E. E. Palmer, Don Malzahn, Lawrence Whitman, Michael J. Jorgensen, Leonidas Deligiannidis, Nita Yodo and Bhaskaran Gopalakrishnan and has published in prestigious journals such as The International Journal of Advanced Manufacturing Technology, Neural Computing and Applications and Engineering Management Journal.

In The Last Decade

Krishna Krishnan

18 papers receiving 299 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Krishna Krishnan United States 9 164 102 90 33 31 21 327
Shuxia Li China 8 133 0.8× 73 0.7× 96 1.1× 28 0.8× 25 0.8× 40 340
Ralph Riedel Germany 9 189 1.2× 77 0.8× 73 0.8× 24 0.7× 18 0.6× 49 340
Tahera Kalsoom United Kingdom 9 149 0.9× 72 0.7× 54 0.6× 35 1.1× 20 0.6× 12 434
Dingzhong Feng China 10 157 1.0× 140 1.4× 96 1.1× 43 1.3× 18 0.6× 30 403
Aditya Akundi United States 6 203 1.2× 56 0.5× 50 0.6× 43 1.3× 21 0.7× 38 375
Immanuel Edinbarough United States 7 196 1.2× 58 0.6× 52 0.6× 24 0.7× 31 1.0× 28 351
Chao Su China 4 220 1.3× 50 0.5× 50 0.6× 37 1.1× 38 1.2× 7 381
Marina Crnjac Croatia 10 309 1.9× 63 0.6× 64 0.7× 44 1.3× 21 0.7× 20 467
Emil Blixt Hansen Denmark 6 124 0.8× 40 0.4× 58 0.6× 35 1.1× 39 1.3× 6 308
Béla Illés Hungary 11 307 1.9× 136 1.3× 93 1.0× 21 0.6× 19 0.6× 73 475

Countries citing papers authored by Krishna Krishnan

Since Specialization
Citations

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

Fields of papers citing papers by Krishna Krishnan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Krishna Krishnan

This figure shows the co-authorship network connecting the top 25 collaborators of Krishna Krishnan. A scholar is included among the top collaborators of Krishna Krishnan 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 Krishna Krishnan. Krishna Krishnan 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.
Boldsaikhan, Enkhsaikhan, et al.. (2025). Soft Robot Workspace Estimation via Finite Element Analysis and Machine Learning. Actuators. 14(3). 110–110.
2.
Boldsaikhan, Enkhsaikhan, et al.. (2024). Soft Robot Design, Manufacturing, and Operation Challenges: A Review. Journal of Manufacturing and Materials Processing. 8(2). 79–79. 10 indexed citations
3.
Boldsaikhan, Enkhsaikhan, et al.. (2023). Robot arm damage detection using vibration data and deep learning. Neural Computing and Applications. 36(4). 1727–1739. 4 indexed citations
4.
Krishnan, Krishna, et al.. (2023). Detection of Small Screws Using Machine Learning. Holmes Museum Of Anthropology (Wichita State University). 13–18. 1 indexed citations
5.
Krishnan, Krishna, et al.. (2022). Examining the impact of E-supply chain on service quality and customer satisfaction: a case study. International Journal of Quality and Service Sciences. 14(2). 274–290. 18 indexed citations
6.
Nannapaneni, Saideep, et al.. (2022). Deep-Learning-Based Cyber-Physical System Framework for Real-Time Industrial Operations. Machines. 10(11). 1001–1001. 3 indexed citations
7.
Krishnan, Krishna, et al.. (2022). Three-stage algorithms for the large-scale dynamic vehicle routing problem with industry 4.0 approach. Journal of Management Analytics. 9(3). 313–329. 5 indexed citations
8.
Alghamdi, Saleh, et al.. (2021). Design of Supply Chain Network to Reduce Impacts of Damages during Shipping. Management and Production Engineering Review. 2 indexed citations
9.
Krishnan, Krishna, et al.. (2021). Heat transfer simulation and improvement of autoclave loading in composites manufacturing. The International Journal of Advanced Manufacturing Technology. 112(11-12). 2989–3000. 13 indexed citations
10.
Krishnan, Krishna, et al.. (2021). Optimising unrelated parallel machine scheduling in job shops with maximum allowable tardiness limit. International Journal of Industrial and Systems Engineering. 37(3). 359–359. 1 indexed citations
11.
Krishnan, Krishna, et al.. (2020). Industry 4.0 in Logistics and Supply Chain Management: A Systematic Literature Review. Engineering Management Journal. 33(3). 187–201. 155 indexed citations
12.
Nannapaneni, Saideep, et al.. (2020). Internet of Things based Cyber-Physical System framework for Real-Time Operations. Holmes Museum Of Anthropology (Wichita State University). 3 indexed citations
13.
Krishnan, Krishna, et al.. (2020). Using Virtual Reality To Address Competency Gaps. Papers on Engineering Education Repository (American Society for Engineering Education). 7.1285.1–7.1285.11. 1 indexed citations
14.
Krishnan, Krishna, et al.. (2020). A two-stage metaheuristic algorithm for the dynamic vehicle routing problem in Industry 4.0 approach. Journal of Management Analytics. 8(1). 69–83. 49 indexed citations
15.
Nannapaneni, Saideep, et al.. (2019). Supervised Machine Learning Approach for Effective Supplier Classification. Holmes Museum Of Anthropology (Wichita State University). 240–245. 9 indexed citations
16.
Krishnan, Krishna, et al.. (2018). Learning Robotic Grasping Strategy Based on Natural-Language Object Descriptions. Holmes Museum Of Anthropology (Wichita State University). 882–887. 19 indexed citations
17.
Wang, Pingfeng, Krishna Krishnan, Janet Twomey, & Nita Yodo. (2018). Risk and Failure Resilience of Interdependent Transportation Systems. 1 indexed citations
18.
Krishnan, Krishna, et al.. (2017). An Integrated Approach for the Analysis of Manufacturing System States. 5(1). 61–72.
19.
Whitman, Lawrence, et al.. (2004). Virtual Reality Case Study throughout the Curriculum to Address Competency Gaps. 19 indexed citations
20.
Deligiannidis, Leonidas, et al.. (2003). JWSU: A Java3D Framework for Virtual Reality.. 312–319. 2 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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