Cong Han

759 citations
36 papers · 387 · 1 hit paper · h-index 11

Impact in

Papers in

Cong Han

36 papers receiving 370 citations

Cong Han's Hit Papers

Dual-path Mamba: Short and Long-term Bidirectional Selective Structured State Space Models for Speech Separation 2025 · 18 citations
180Years since publication51015

Peers

Cong Han
Comparison fields: 5 of 52
  • Signal Processing 245
  • Artificial Intelligence 161
  • Cognitive Neuroscience 89
  • Computational Mechanics 61
  • Computer Vision and Pattern Recognition 57
Replace Abhishek Sehgal with:
Abhishek Sehgal United States
Hsiu-Wen Chang Taiwan
Kaustubh Kalgaonkar United States
Romain Serizel France
Yoshihisa Nakatoh Japan
Thi Ngoc Tho Nguyen Singapore
Christoph Pörschmann Germany
Fabian-Robert Stöter Germany
Dongsuk Yook South Korea
Nicoleta Roman United States
Cong Han relative to Abhishek Sehgal United States Abhishek Sehgal's profile →
Citations per field
00.5×4.4×
Abhishek Sehgal · 1×
Citations per year

Countries citing papers authored by Cong Han

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201980
2 201954
3 202030
4 202220
5
Dual-path Mamba: Short and Long-term Bidirectional Selective Structured State Space Models for Speech Separation
Hit paper breakdown →
202518
6 202318
7 202117
8 202115
9 201913
10 202112
11 202311
12 20258
13 20237
14 20217
15 20217
16 20216
17 20236
18 20206
19 20236
20 20216

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 387 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 Biometric Identification and Security (2 papers). The work is most often cited by research in Signal Processing (245 citations), Artificial Intelligence (161 citations), Cognitive Neuroscience (89 citations), Computational Mechanics (61 citations) and Computer Vision and Pattern Recognition (57 citations). Cong Han has collaborated with scholars based in United States, China and Finland. Frequent co-authors include Nima Mesgarani, Yi Luo, Enea Ceolini, Shih‐Chii Liu, Ashesh D. Mehta, Jose L. Herrero, Ziming Kou, James O’Sullivan, Juan Wu and Lei Zuo. Their work appears in journals such as Neurocomputing, Applied Sciences, Sensors, Measurement 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.

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