Jay F. Tu

2.4k total citations · 1 hit paper
67 papers, 1.9k citations indexed

About

Jay F. Tu is a scholar working on Mechanical Engineering, Computational Mechanics and Electrical and Electronic Engineering. According to data from OpenAlex, Jay F. Tu has authored 67 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Mechanical Engineering, 20 papers in Computational Mechanics and 12 papers in Electrical and Electronic Engineering. Recurrent topics in Jay F. Tu's work include Advanced Measurement and Metrology Techniques (20 papers), Advanced machining processes and optimization (19 papers) and Welding Techniques and Residual Stresses (15 papers). Jay F. Tu is often cited by papers focused on Advanced Measurement and Metrology Techniques (20 papers), Advanced machining processes and optimization (19 papers) and Welding Techniques and Residual Stresses (15 papers). Jay F. Tu collaborates with scholars based in United States, Japan and Sweden. Jay F. Tu's co-authors include M. Corless, Chi‐Wei Lin, Jeffrey L. Stein, Mark Gartner, Isamu Miyamoto, Takashi Inoue, Keng H. Leong, James B. Taylor, Pal Molian and Etsuji Ohmura and has published in prestigious journals such as SHILAP Revista de lepidopterología, Carbon and Automatica.

In The Last Decade

Jay F. Tu

64 papers receiving 1.8k citations

Hit Papers

State and Input Estimation for a Class of Uncertain Systems 1998 2026 2007 2016 1998 100 200 300 400
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. State and Input Estimation for a Class of Uncertain Systems
    1998 462 citations M. Corless, Jay F. Tu Automatica profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jay F. Tu United States 19 1.3k 528 264 242 225 67 1.9k
An‐Chen Lee Taiwan 23 879 0.7× 804 1.5× 306 1.2× 221 0.9× 75 0.3× 93 1.4k
Arthur W. Lees United Kingdom 25 1.9k 1.5× 1.5k 2.9× 115 0.4× 268 1.1× 554 2.5× 87 2.7k
Deyong You China 24 1.6k 1.2× 193 0.4× 345 1.3× 114 0.5× 518 2.3× 55 2.0k
J.R.R. Mayer Canada 28 2.1k 1.6× 162 0.3× 910 3.4× 443 1.8× 178 0.8× 114 2.3k
Andreas Steinboeck Austria 17 481 0.4× 463 0.9× 252 1.0× 65 0.3× 343 1.5× 117 984
Meng-Shiun Tsai Taiwan 17 566 0.4× 765 1.4× 449 1.7× 227 0.9× 64 0.3× 53 1.2k
Shijing Wu China 14 332 0.3× 396 0.8× 101 0.4× 115 0.5× 125 0.6× 62 854
Satoshi KIYONO Japan 21 1.4k 1.1× 238 0.5× 510 1.9× 766 3.2× 85 0.4× 112 1.7k
Elijah Kannatey‐Asibu United States 22 1.5k 1.2× 174 0.3× 339 1.3× 371 1.5× 398 1.8× 69 1.9k
Hong Lü China 15 415 0.3× 188 0.4× 65 0.2× 163 0.7× 121 0.5× 134 760

Countries citing papers authored by Jay F. Tu

Since Specialization
Citations

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

Fields of papers citing papers by Jay F. Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay F. Tu. 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 Jay F. Tu. The network helps show where Jay F. Tu may publish in the future.

Co-authorship network of co-authors of Jay F. Tu

This figure shows the co-authorship network connecting the top 25 collaborators of Jay F. Tu. A scholar is included among the top collaborators of Jay F. Tu 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 Jay F. Tu. Jay F. Tu 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.
Tu, Jay F., et al.. (2023). A novel auto-gaping magnetic pole system for inner surface finishing of non-circular pipes using magnetic abrasive finishing process. Journal of Magnetism and Magnetic Materials. 580. 170909–170909. 10 indexed citations
2.
Tu, Jay F., et al.. (2022). Digital Synthesis of Realistically Clustered Carbon Nanotubes. SHILAP Revista de lepidopterología. 8(3). 34–34. 3 indexed citations
3.
Tu, Jay F., et al.. (2019). Feasibility Study of Microneedle Fabrication from a thin Nitinol Wire Using a CW Single-Mode Fiber Laser. Open Engineering. 9(1). 167–177. 12 indexed citations
4.
Tu, Jay F., et al.. (2018). Molecular dynamics simulations of the wetting behavior of carbon nanotubes in liquid copper. Computers & Fluids. 172. 19–28. 3 indexed citations
5.
Tu, Jay F., et al.. (2010). Inherent instability investigation for low speed laser welding of aluminum using a single-mode fiber laser. Journal of Materials Processing Technology. 210(10). 1411–1418. 24 indexed citations
6.
Tu, Jay F., et al.. (2007). A Practical method for determining the beam profile near the focal spot. The International Journal of Advanced Manufacturing Technology. 37(11-12). 1113–1119. 10 indexed citations
7.
Tu, Jay F., Takashi Inoue, & Isamu Miyamoto. (2002). Quantitative characterization of keyhole absorption mechanisms in 20 kW-class CO2 laser welding processes. Journal of Physics D Applied Physics. 36(2). 192–203. 26 indexed citations
8.
Tu, Jay F., et al.. (2002). Conceptual Design of Machine Tool Interfaces for High-Speed Machining. Journal of Manufacturing Processes. 4(1). 16–27. 9 indexed citations
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11.
Tu, Jay F., et al.. (1999). A thermal model for high speed motorized spindles. International Journal of Machine Tools and Manufacture. 39(9). 1345–1366. 249 indexed citations
12.
Tu, Jay F., et al.. (1999). Laser Weld Penetration Estimation Using Temperature Measurements. Journal of Manufacturing Science and Engineering. 121(2). 179–188. 17 indexed citations
13.
Tu, Jay F., et al.. (1998). A Power Flow Model for High Speed Motorized Spindles: Heat Generation Characterization. Dynamic Systems and Control. 415–422. 4 indexed citations
14.
Corless, M. & Jay F. Tu. (1998). State and Input Estimation for a Class of Uncertain Systems. Automatica. 34(6). 757–764. 462 indexed citations breakdown →
15.
Tu, Jay F., et al.. (1997). Predictive maintenance of an industrial laser using statistical process control charting. C57–C66. 5 indexed citations
16.
17.
Tu, Jay F., et al.. (1996). A model for estimating penetration depth of laser welding processes. Journal of Physics D Applied Physics. 29(7). 1831–1841. 115 indexed citations
18.
Tu, Jay F., et al.. (1996). Model-based penetration depth estimation for laser welding processes. B116–B125. 2 indexed citations
19.
Tu, Jay F., et al.. (1996). Bearing Condition Monitoring for Preventive Maintenance in a Production Environment. Tribology Transactions. 39(4). 936–942. 16 indexed citations
20.
Tu, Jay F. & Jeffrey L. Stein. (1995). On-Line Preload Monitoring for Anti-Friction Spindle Beatings of High-Speed Machine Tools. Journal of Dynamic Systems Measurement and Control. 117(1). 43–53. 29 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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