Hien Van Nguyen

3.7k total citations
70 papers, 2.0k citations indexed

About

Hien Van Nguyen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Hien Van Nguyen has authored 70 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Vision and Pattern Recognition, 20 papers in Artificial Intelligence and 8 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Hien Van Nguyen's work include Domain Adaptation and Few-Shot Learning (8 papers), COVID-19 diagnosis using AI (6 papers) and AI in cancer detection (6 papers). Hien Van Nguyen is often cited by papers focused on Domain Adaptation and Few-Shot Learning (8 papers), COVID-19 diagnosis using AI (6 papers) and AI in cancer detection (6 papers). Hien Van Nguyen collaborates with scholars based in United States, Canada and France. Hien Van Nguyen's co-authors include Vishal M. Patel, Rama Chellappa, Renè Vidal, Aryan Mobiny, Nasser M. Nasrabadi, Amit Banerjee, Sumit Shekhar, Ngan Le, Khoa Luu and Nicholas Ayache and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and ACS Nano.

In The Last Decade

Hien Van Nguyen

67 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hien Van Nguyen United States 25 839 605 332 285 225 70 2.0k
Xianghua Xie United Kingdom 25 1.4k 1.7× 633 1.0× 299 0.9× 291 1.0× 315 1.4× 146 2.8k
Tao Wan China 27 1.0k 1.2× 719 1.2× 192 0.6× 414 1.5× 367 1.6× 154 2.6k
Paul Honeiné France 21 540 0.6× 844 1.4× 451 1.4× 322 1.1× 203 0.9× 75 2.1k
Martín Arjovsky United States 4 1.5k 1.8× 1.0k 1.7× 127 0.4× 223 0.8× 183 0.8× 4 2.8k
Shihui Ying China 24 1.0k 1.2× 670 1.1× 201 0.6× 184 0.6× 435 1.9× 124 2.2k
Rui Huang China 23 2.0k 2.3× 390 0.6× 201 0.6× 509 1.8× 322 1.4× 111 2.8k
Arif Mahmood Pakistan 28 1.7k 2.1× 887 1.5× 130 0.4× 375 1.3× 168 0.7× 121 2.7k
Georgios Tziritas Greece 26 2.2k 2.6× 480 0.8× 161 0.5× 332 1.2× 246 1.1× 73 2.9k
Xinzhong Zhu China 23 1.4k 1.7× 958 1.6× 141 0.4× 434 1.5× 176 0.8× 97 2.3k

Countries citing papers authored by Hien Van Nguyen

Since Specialization
Citations

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

Fields of papers citing papers by Hien Van Nguyen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hien Van Nguyen. 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 Hien Van Nguyen. The network helps show where Hien Van Nguyen may publish in the future.

Co-authorship network of co-authors of Hien Van Nguyen

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

All Works

20 of 20 papers shown
1.
Pownall, Henry J., Vittorio Cristini, Daniela I. Staquicini, et al.. (2025). Rational Design of Safer Inorganic Nanoparticles via Mechanistic Modeling-Informed Machine Learning. ACS Nano. 19(23). 21538–21555. 4 indexed citations
2.
Vu, Tuan A., Ngan Le, Zhigang Deng, et al.. (2025). Modeling radiologists’ cognitive processes using a digital gaze twin to enhance radiology training. Scientific Reports. 15(1). 13685–13685.
3.
Maric, Dragan, et al.. (2024). Cellular data extraction from multiplexed brain imaging data using self-supervised Dual-loss Adaptive Masked Autoencoder. Artificial Intelligence in Medicine. 151. 102828–102828. 1 indexed citations
4.
Wu, Carol C., Hien Van Nguyen, Zhigang Deng, et al.. (2024). ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions. Artificial Intelligence in Medicine. 160. 103054–103054. 1 indexed citations
5.
Eccher, Albino, Ilaria Girolami, Vincenzo L’Imperio, et al.. (2023). Time for a full digital approach in nephropathology: a systematic review of current artificial intelligence applications and future directions. Journal of Nephrology. 37(1). 65–76. 12 indexed citations
6.
Nguyen, Hien Van, et al.. (2023). Evaluating and Improving Domain Invariance in Contrastive Self-Supervised Learning by Extrapolating the Loss Function. IEEE Access. 11. 137758–137768. 1 indexed citations
7.
Wang, Shirui, et al.. (2022). Self-Supervised Learning for Efficient Antialiasing Seismic Data Interpolation. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–19. 15 indexed citations
8.
Maric, Dragan, et al.. (2021). Whole-brain tissue mapping toolkit using large-scale highly multiplexed immunofluorescence imaging and deep neural networks. Nature Communications. 12(1). 1550–1550. 51 indexed citations
9.
Mobiny, Aryan, Pietro Antonio Cicalese, Naveen Garg, et al.. (2021). Memory-Augmented Capsule Network for Adaptable Lung Nodule Classification. IEEE Transactions on Medical Imaging. 40(10). 2869–2879. 21 indexed citations
10.
Wang, Shirui, et al.. (2021). Self-supervised learning for anti-aliasing seismic data interpolation. 1500–1504. 8 indexed citations
11.
Wang, Shirui, et al.. (2020). A robust first-arrival picking workflow using convolutional and recurrent neural networks. Geophysics. 85(5). U109–U119. 44 indexed citations
12.
Cicalese, Pietro Antonio, et al.. (2020). Kidney Level Lupus Nephritis Classification Using Uncertainty Guided Bayesian Convolutional Neural Networks. IEEE Journal of Biomedical and Health Informatics. 25(2). 315–324. 22 indexed citations
13.
Becker, Jan U., David Mayerich, Jonathan Barratt, et al.. (2020). Artificial intelligence and machine learning in nephropathology. Kidney International. 98(1). 65–75. 70 indexed citations
14.
Rezvan, Ali, et al.. (2019). Phasetime: Deep Learning Approach to Detect Nuclei in Time Lapse Phase Images. Journal of Clinical Medicine. 8(8). 1159–1159. 12 indexed citations
15.
Nguyen, Hien Van, et al.. (2019). Physician-Friendly Machine Learning: A Case Study with Cardiovascular Disease Risk Prediction. Journal of Clinical Medicine. 8(7). 1050–1050. 51 indexed citations
16.
Wang, Qian, Fausto Milletarì, Hien Van Nguyen, et al.. (2019). Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings. 4 indexed citations
17.
Mobiny, Aryan, Hengyang Lu, Hien Van Nguyen, Badrinath Roysam, & Navin Varadarajan. (2019). Automated Classification of Apoptosis in Phase Contrast Microscopy Using Capsule Network. IEEE Transactions on Medical Imaging. 39(1). 1–10. 46 indexed citations
18.
Walsh, Michael J., et al.. (2018). Deep learning for FTIR histology: leveraging spatial and spectral features with convolutional neural networks. The Analyst. 144(5). 1642–1653. 72 indexed citations
19.
Zhang, Huaqing, et al.. (2017). Stacked LSTM Deep Learning Model for Traffic Prediction in Vehicle-to-Vehicle Communication. 1–5. 55 indexed citations
20.
Nguyen, Hien Van. (1993). Video coding and modeling with applications to ATM multiplexing. PhDT. 1 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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