Tim Ng
- Signal Processing top 2%
- Speech and Audio Processing 16
- Music and Audio Processing 11
- Artificial Intelligence top 5%
- Speech Recognition and Synthesis 25
- Natural Language Processing Techniques 10
- Topic Modeling 6
- Speech and dialogue systems 2
- Advanced Text Analysis Techniques 1
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- Orthopedic Surgery and Rehabilitation 1
- Co-authors
- Long NguyenPavel MatějkaRoger HsiaoLe ZhangBing ZhangStavros TsakalidisKarel VeselýJeff Ma
- Journals
- IEEE Signal Processing Letters (1 paper)Annals of Plastic Surgery (1 paper)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (1 paper)
- Partner nations
- United StatesCzechiaFrance
In The Last Decade
Tim Ng
29 papers receiving 416 citations
Peers
Comparison fields: 5 of 54
- Signal Processing 310
- Artificial Intelligence 470
- Experimental and Cognitive Psychology 16
- Pharmacy 6
- Computer Vision and Pattern Recognition 23
Countries citing papers authored by Tim Ng
This map shows the geographic impact of Tim Ng'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 Tim Ng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Ng more than expected).
Fields of papers citing papers by Tim Ng
This network shows the impact of papers produced by Tim Ng. 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 Tim Ng. The network helps show where Tim Ng may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tim Ng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2024 | 3 | |
| 3 | 2023 | 1 | |
| 4 | 2020 | 10 | |
| 5 | 2017 | 1 | |
| 6 | 2017 | 7 | |
| 7 | 2017 | 5 | |
| 8 | 2016 | 13 | |
| 9 | 2013 | 18 | |
| 10 | 2013 | 77 | |
| 11 | 2013 | 19 | |
| 12 | 2012 | 13 | |
| 13 | 2012 | 81 | |
| 14 | 2011 | 6 | |
| 15 | 2010 | 4 | |
| 16 | 2009 | 9 | |
| 17 | 2009 | 5 | |
| 18 | 2008 | 9 | |
| 19 | Introducing the MONIAC: An Early and Innovative Economic Model | 2007 | 3 |
| 20 | 2007 | 49 |
About Tim Ng
Tim Ng is a scholar working on Signal Processing, Artificial Intelligence, General Economics, Econometrics and Finance, Experimental and Cognitive Psychology and Epidemiology, having authored 30 papers that have together received 531 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (25 papers), Speech and Audio Processing (16 papers), Music and Audio Processing (11 papers), Natural Language Processing Techniques (10 papers), Topic Modeling (6 papers), Speech and dialogue systems (2 papers), Orthopedic Surgery and Rehabilitation (1 paper) and Advanced Text Analysis Techniques (1 paper). The work is most often cited by research in Signal Processing (310 citations), Artificial Intelligence (470 citations), Experimental and Cognitive Psychology (16 citations), Pharmacy (6 citations) and Computer Vision and Pattern Recognition (23 citations). Tim Ng has collaborated with scholars based in United States, Czechia and France. Frequent co-authors include Long Nguyen, Pavel Matějka, Roger Hsiao, Le Zhang, Bing Zhang, Stavros Tsakalidis, Karel Veselý, Jeff Ma, Sri Harish Mallidi and Spyros Matsoukas. Their work appears in journals such as IEEE Signal Processing Letters, Annals of Plastic Surgery, Rare & Special e-Zone (The Hong Kong University of Science and Technology), Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing and Reserve Bank of New Zealand Bulletin.
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.