Jaydeep Karandikar

1.1k total citations
46 papers, 791 citations indexed

About

Jaydeep Karandikar is a scholar working on Mechanical Engineering, Industrial and Manufacturing Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Jaydeep Karandikar has authored 46 papers receiving a total of 791 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Mechanical Engineering, 22 papers in Industrial and Manufacturing Engineering and 7 papers in Electrical and Electronic Engineering. Recurrent topics in Jaydeep Karandikar's work include Advanced machining processes and optimization (30 papers), Manufacturing Process and Optimization (19 papers) and Advanced Measurement and Metrology Techniques (15 papers). Jaydeep Karandikar is often cited by papers focused on Advanced machining processes and optimization (30 papers), Manufacturing Process and Optimization (19 papers) and Advanced Measurement and Metrology Techniques (15 papers). Jaydeep Karandikar collaborates with scholars based in United States, United Kingdom and Austria. Jaydeep Karandikar's co-authors include Tony L. Schmitz, Ali E. Abbas, Thomas R. Kurfess, Scott Smith, Mohamed El Mansori, Chandra Nath, Sam Turner, Thomas E. McLeay, Nam Ho Kim and Andrew Honeycutt and has published in prestigious journals such as Mechanical Systems and Signal Processing, CIRP Annals and Engineering Fracture Mechanics.

In The Last Decade

Jaydeep Karandikar

42 papers receiving 756 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jaydeep Karandikar United States 15 632 301 286 155 83 46 791
Roger Serra France 13 428 0.7× 227 0.8× 141 0.5× 132 0.9× 69 0.8× 57 682
Xinyong Mao China 20 958 1.5× 259 0.9× 335 1.2× 299 1.9× 158 1.9× 75 1.1k
Tongshun Liu China 10 394 0.6× 196 0.7× 135 0.5× 117 0.8× 142 1.7× 21 541
Songping He China 16 483 0.8× 157 0.5× 229 0.8× 136 0.9× 91 1.1× 37 652
Xingwei Xu China 10 524 0.8× 306 1.0× 182 0.6× 98 0.6× 240 2.9× 15 767
X.D. Fang Australia 19 625 1.0× 240 0.8× 288 1.0× 236 1.5× 47 0.6× 45 823
P.M. Lister United Kingdom 10 586 0.9× 354 1.2× 196 0.7× 278 1.8× 61 0.7× 14 714
Pierre Dehombreux Belgium 12 366 0.6× 111 0.4× 123 0.4× 64 0.4× 130 1.6× 42 527
Zhengrui Tao China 6 390 0.6× 197 0.7× 111 0.4× 81 0.5× 141 1.7× 11 524

Countries citing papers authored by Jaydeep Karandikar

Since Specialization
Citations

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

Fields of papers citing papers by Jaydeep Karandikar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaydeep Karandikar

This figure shows the co-authorship network connecting the top 25 collaborators of Jaydeep Karandikar. A scholar is included among the top collaborators of Jaydeep Karandikar 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 Jaydeep Karandikar. Jaydeep Karandikar 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.
Karandikar, Jaydeep, et al.. (2025). An analytical model integrating tool kinematics and material flow for the spindle torque prediction in additive friction stir deposition. Manufacturing Letters. 44. 1177–1186. 1 indexed citations
2.
Karandikar, Jaydeep, et al.. (2025). A cutting mechanics-based machine learning modeling method to discover governing equations of machining dynamics. Manufacturing Letters. 44. 759–769.
3.
Karandikar, Jaydeep, et al.. (2025). Part distortion monitoring in additive manufacturing using machining. Additive Manufacturing Letters. 14. 100295–100295. 1 indexed citations
4.
Jared, Bradley Howell, et al.. (2024). Chatter detection in simulated machining data: a simple refined approach to vibration data. The International Journal of Advanced Manufacturing Technology. 132(9-10). 4541–4557. 7 indexed citations
5.
Karandikar, Jaydeep, et al.. (2024). Bayesian stability and force modeling for uncertain machining processes. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1(1). 3 indexed citations
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Karandikar, Jaydeep, et al.. (2024). Using GANs to predict milling stability from limited data. Journal of Intelligent Manufacturing. 36(2). 1201–1235. 4 indexed citations
9.
Qu, Yongzhi, et al.. (2024). Cutting force estimation from machine learning and physics-inspired data-driven models utilizing accelerometer measurements. Procedia CIRP. 126. 318–323. 3 indexed citations
10.
Haley, James, et al.. (2023). Review of in situ process monitoring for metal hybrid directed energy deposition. Journal of Manufacturing Processes. 109. 128–139. 19 indexed citations
11.
Karandikar, Jaydeep, Jamie Coble, Bradley Howell Jared, et al.. (2023). Predicting chatter using machine learning and acoustic signals from low-cost microphones. The International Journal of Advanced Manufacturing Technology. 125(11-12). 5503–5518. 4 indexed citations
12.
Karandikar, Jaydeep, Kyle Saleeby, Thomas Feldhausen, et al.. (2022). Evaluation of automated stability testing in machining through closed-loop control and Bayesian machine learning. Mechanical Systems and Signal Processing. 181. 109531–109531. 6 indexed citations
13.
Karandikar, Jaydeep, et al.. (2022). Physics-informed Bayesian machine learning case study: Integral blade rotors. Journal of Manufacturing Processes. 85. 503–514. 5 indexed citations
14.
Karandikar, Jaydeep, et al.. (2021). Propagation of Johnson-Cook flow stress model uncertainty to milling force uncertainty using finite element analysis and time domain simulation. Procedia Manufacturing. 53. 223–235. 7 indexed citations
15.
Schmitz, Tony L., et al.. (2020). Uncertainty evaluation for twist drilling stability model. Precision Engineering. 66. 324–332. 3 indexed citations
16.
Karandikar, Jaydeep. (2019). Machine learning classification for tool life modeling using production shop-floor tool wear data. Procedia Manufacturing. 34. 446–454. 21 indexed citations
17.
Karandikar, Jaydeep, et al.. (2016). Tool life predictions in milling using spindle power with the neural network technique. Journal of Manufacturing Processes. 22. 161–168. 176 indexed citations
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19.
Karandikar, Jaydeep, Thomas E. McLeay, Sam Turner, & Tony L. Schmitz. (2013). Remaining Useful Tool Life Predictions Using Bayesian Inference. 5 indexed citations
20.
Lee, Joseph H. W., et al.. (1998). Hydraulics of “Duckbill” Elastomer Check Valves. Journal of Hydraulic Engineering. 124(4). 394–405. 13 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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