Sifei Han

464 total citations
10 papers, 199 citations indexed

About

Sifei Han is a scholar working on Artificial Intelligence, Molecular Biology and General Health Professions. According to data from OpenAlex, Sifei Han has authored 10 papers receiving a total of 199 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 2 papers in Molecular Biology and 2 papers in General Health Professions. Recurrent topics in Sifei Han's work include Topic Modeling (6 papers), Machine Learning in Healthcare (3 papers) and Natural Language Processing Techniques (3 papers). Sifei Han is often cited by papers focused on Topic Modeling (6 papers), Machine Learning in Healthcare (3 papers) and Natural Language Processing Techniques (3 papers). Sifei Han collaborates with scholars based in United States, China and Canada. Sifei Han's co-authors include Ramakanth Kavuluru, Russell Richie, Fuchiang Tsui, Lingyun Shi, Neal D. Ryan, David A. Brent, Wei Quan, Andrew S. Tseng, Anthony Rios and Filip Ginter and has published in prestigious journals such as PLoS ONE, IEEE Access and Information Sciences.

In The Last Decade

Sifei Han

9 papers receiving 191 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sifei Han United States 8 103 48 36 27 25 10 199
Serena Jeblee Canada 7 187 1.8× 69 1.4× 17 0.5× 17 0.6× 14 0.6× 12 280
Shan Chen United States 5 105 1.0× 25 0.5× 34 0.9× 23 0.9× 17 0.7× 9 231
Clive Stringer United Kingdom 5 83 0.8× 68 1.4× 29 0.8× 42 1.6× 9 0.4× 6 233
Rubina Rizvi United States 11 43 0.4× 50 1.0× 65 1.8× 21 0.8× 10 0.4× 29 259
Cyril Grouin France 13 321 3.1× 239 5.0× 19 0.5× 22 0.8× 10 0.4× 49 488
Xu Jie China 8 65 0.6× 22 0.5× 65 1.8× 18 0.7× 19 0.8× 26 261
Kevin Lybarger United States 9 101 1.0× 36 0.8× 64 1.8× 39 1.4× 24 1.0× 31 236
Tiffany I. Leung United States 6 70 0.7× 43 0.9× 69 1.9× 11 0.4× 14 0.6× 25 251
Anahita Davoudi United States 9 70 0.7× 12 0.3× 44 1.2× 21 0.8× 10 0.4× 30 208
Archana Tapuria United Kingdom 6 106 1.0× 100 2.1× 65 1.8× 13 0.5× 4 0.2× 18 299

Countries citing papers authored by Sifei Han

Since Specialization
Citations

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

Fields of papers citing papers by Sifei Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sifei Han

This figure shows the co-authorship network connecting the top 25 collaborators of Sifei Han. A scholar is included among the top collaborators of Sifei Han 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 Sifei Han. Sifei Han is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
2.
Han, Sifei, Russell Richie, Lingyun Shi, & Fuchiang Tsui. (2024). Automated Matchmaking of Researcher Biosketches and Funder Requests for Proposals Using Deep Neural Networks. IEEE Access. 12. 98096–98106. 2 indexed citations
3.
Richie, Russell, Vı́ctor Ruiz, Sifei Han, Lingyun Shi, & Fuchiang Tsui. (2023). Extracting social determinants of health events with transformer-based multitask, multilabel named entity recognition. Journal of the American Medical Informatics Association. 30(8). 1379–1388. 12 indexed citations
4.
Han, Sifei, Lingyun Shi, Russell Richie, et al.. (2022). Classifying social determinants of health from unstructured electronic health records using deep learning-based natural language processing. Journal of Biomedical Informatics. 127. 103984–103984. 74 indexed citations
5.
Han, Sifei, Lingyun Shi, Russell Richie, & Fuchiang Tsui. (2022). Building siamese attention-augmented recurrent convolutional neural networks for document similarity scoring. Information Sciences. 615. 90–102. 8 indexed citations
6.
Meng, Xia, Anxin Wang, Guojun Zhang, et al.. (2021). Analytical validation of GMEX rapid point-of-care CYP2C19 genotyping system for the CHANCE-2 trial. Stroke and Vascular Neurology. 6(2). 274–279. 7 indexed citations
7.
Sarker, Abeed, Maksim Belousov, Kai Hakala, et al.. (2018). Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task. Journal of the American Medical Informatics Association. 25(10). 1274–1283. 61 indexed citations
8.
Han, Sifei, et al.. (2017). Team UKNLP: Detecting ADRs, Classifying Medication Intake Messages, and Normalizing ADR Mentions on Twitter.. 49–53. 10 indexed citations
9.
Han, Sifei & Ramakanth Kavuluru. (2016). Exploratory Analysis of Marketing and Non-marketing E-cigarette Themes on Twitter. Lecture notes in computer science. 10047. 307–322. 13 indexed citations
10.
Kavuluru, Ramakanth, Sifei Han, & Daniel R. Harris. (2013). Unsupervised Extraction of Diagnosis Codes from EMRs Using Knowledge-Based and Extractive Text Summarization Techniques. Lecture notes in computer science. 7884. 77–88. 12 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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2026