Tom Kwan

600 citations
18 papers · 428 · h-index 9

Impact in

Papers in

Tom Kwan

16 papers receiving 397 citations

Peers

Tom Kwan
Comparison fields: 5 of 38
  • Signal Processing 158
  • Computational Mechanics 162
  • Biomedical Engineering 204
  • Electrical and Electronic Engineering 237
  • Computer Vision and Pattern Recognition 51
Replace Dayong Zhou with:
Dayong Zhou United States
Fu‐Kun Chen Taiwan
D.J. Shpak Canada
Lifu Wu China
Cheung-Fat Chan Hong Kong
Shunliang Mei China
Marcus Zeller Germany
Jehad Ababneh Jordan
Jie Zhuang China
Tom Kwan relative to Dayong Zhou United States Dayong Zhou's profile →
Citations per field
00.5×6.4×
Dayong Zhou · 1×
Citations per year

Countries citing papers authored by Tom Kwan

Since Specialization
Citations

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

Fields of papers citing papers by Tom Kwan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Tom Kwan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tom Kwan Line = papers co-authored together Tom Kwan links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 1989188
2 199168
3 199648
4 201436
5 201522
6 199914
7 199410
8 20079
9 19999
10
Theory and VLSI architectures for asynchronous sample-rate converters
19936
11
A dual-channel 10b 80MS/s pipeline ADC with 0.16mm 2 area in 65nm CMOS
20096
12 20034
13 19953
14 20032
15 20021
16 20021
17 20021
18 20080

About Tom Kwan

Tom Kwan is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Signal Processing, Computational Mechanics and Ocean Engineering, having authored 18 papers that have together received 428 indexed citations. Recurring topics across this work include Analog and Mixed-Signal Circuit Design (11 papers), Advancements in PLL and VCO Technologies (8 papers), Advanced Adaptive Filtering Techniques (6 papers), Digital Filter Design and Implementation (3 papers), Blind Source Separation Techniques (3 papers), CCD and CMOS Imaging Sensors (3 papers), Speech and Audio Processing (3 papers) and Advancements in Semiconductor Devices and Circuit Design (2 papers). The work is most often cited by research in Signal Processing (158 citations), Computational Mechanics (162 citations), Biomedical Engineering (204 citations), Electrical and Electronic Engineering (237 citations) and Computer Vision and Pattern Recognition (51 citations). Tom Kwan has collaborated with scholars based in United States, Israel and Netherlands. Frequent co-authors include K. Martin, Robert Adams, Feng Su, Xinyu Yu, Xinyu Yu, Fang Lin, Kevin Li, H. Samueli, R. Hawley and Fang Lü. Their work appears in journals such as IEEE Journal of Solid-State Circuits, Journal of the Audio Engineering Society, IEEE Transactions on Communications, IEEE Transactions on Circuits and Systems and Offshore Technology Conference.

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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