Cong Han
Impact in
- Signal Processing top 2%
- Speech and Audio Processing
- Music and Audio Processing
- Blind Source Separation Techniques
- Artificial Intelligence top 10%
- Speech Recognition and Synthesis
- Topic Modeling
Papers in
-
- Speech and Audio Processing 20
- Music and Audio Processing 15
-
- Speech Recognition and Synthesis 16
- Co-authors
- Nima Mesgarani (21 shared papers)Yi Luo (12 shared papers)Shih‐Chii Liu (1 shared paper)Enea Ceolini (1 shared paper)Ashesh D. Mehta (3 shared papers)Ziming Kou (5 shared papers)James O’Sullivan (1 shared paper)Jose L. Herrero (2 shared papers)
- Journals
- Applied Sciences (2 papers)Neurocomputing (2 papers)Sensors (2 papers)Advanced Science (1 paper)IEEE Journal of Selected Topics in Signal Processing (1 paper)
- Partner nations
- United StatesChinaFinland
In The Last Decade
Cong Han
36 papers receiving 406 citations
Cong Han's Hit Papers
Peers
Comparison fields: 5 of 56
- Signal Processing 254
- Artificial Intelligence 168
- Cognitive Neuroscience 90
- Computational Mechanics 65
- Computer Vision and Pattern Recognition 58
Countries citing papers authored by Cong Han
This map shows the geographic impact of Cong Han'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 Cong Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cong Han more than expected).
Fields of papers citing papers by Cong Han
This network shows the impact of papers produced by Cong Han. 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 Cong Han. The network helps show where Cong Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Cong Han, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 85 | |
| 2 | 2019 | 57 | |
| 3 | 2020 | 33 | |
| 4 | 2022 | 25 | |
| 5 | Dual-path Mamba: Short and Long-term Bidirectional Selective Structured State Space Models for Speech Separation Hit paper breakdown → | 2025 | 21 |
| 6 | 2023 | 19 | |
| 7 | 2021 | 19 | |
| 8 | 2021 | 15 | |
| 9 | 2023 | 14 | |
| 10 | 2019 | 13 | |
| 11 | 2021 | 12 | |
| 12 | 2025 | 10 | |
| 13 | 2023 | 8 | |
| 14 | 2021 | 7 | |
| 15 | 2023 | 7 | |
| 16 | 2021 | 7 | |
| 17 | 2021 | 6 | |
| 18 | 2024 | 6 | |
| 19 | 2023 | 6 | |
| 20 | 2021 | 6 |
About Cong Han
Cong Han is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Cognitive Neuroscience and Mechanical Engineering, having authored 36 papers that have together received 424 indexed citations. Recurring topics across this work include Speech and Audio Processing (20 papers), Speech Recognition and Synthesis (16 papers), Music and Audio Processing (15 papers), Hearing Loss and Rehabilitation (5 papers), Mineral Processing and Grinding (4 papers), Belt Conveyor Systems Engineering (3 papers), Phonetics and Phonology Research (2 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). The work is most often cited by research in Signal Processing (254 citations), Artificial Intelligence (168 citations), Cognitive Neuroscience (90 citations), Computational Mechanics (65 citations) and Computer Vision and Pattern Recognition (58 citations). Cong Han has collaborated with scholars based in United States, China and Finland. Frequent co-authors include Nima Mesgarani, Yi Luo, Shih‐Chii Liu, Enea Ceolini, Ashesh D. Mehta, Ziming Kou, James O’Sullivan, Jose L. Herrero, Juan Wu and Lei Zuo. Their work appears in journals such as Applied Sciences, Neurocomputing, Sensors, Advanced Science and IEEE Journal of Selected Topics in Signal Processing.
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.