Xiao Da

3.0k total citations · 1 hit paper
51 papers, 1.7k citations indexed

About

Xiao Da is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Genetics. According to data from OpenAlex, Xiao Da has authored 51 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Artificial Intelligence and 8 papers in Genetics. Recurrent topics in Xiao Da's work include Glioma Diagnosis and Treatment (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers) and MRI in cancer diagnosis (7 papers). Xiao Da is often cited by papers focused on Glioma Diagnosis and Treatment (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers) and MRI in cancer diagnosis (7 papers). Xiao Da collaborates with scholars based in United States, China and Norway. Xiao Da's co-authors include Christos Davatzikos, Mehdi Mirza, Aaron Courville, Yoshua Bengio, Ian Goodfellow, Hamed Akbari, Michel Bilello, Yangming Ou, Donald M. O’Rourke and Ronald L. Wolf and has published in prestigious journals such as Nature Communications, PLoS ONE and Brain.

In The Last Decade

Xiao Da

50 papers receiving 1.7k citations

Hit Papers

An Empirical Investigation of Catastrophic Forgetting in ... 2014 2026 2018 2022 2014 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
    2014 341 citations Ian Goodfellow, Mehdi Mirza et al. arXiv (Cornell University) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiao Da United States 19 558 466 351 316 312 51 1.7k
Saima Rathore United States 19 796 1.4× 416 0.9× 362 1.0× 84 0.3× 217 0.7× 54 1.4k
Junfeng Lu China 24 579 1.0× 177 0.4× 420 1.2× 132 0.4× 59 0.2× 80 1.6k
Junko Takahashi Japan 20 416 0.7× 211 0.5× 73 0.2× 345 1.1× 133 0.4× 62 1.9k
Mohamed Akil France 30 601 1.1× 124 0.3× 78 0.2× 99 0.3× 328 1.1× 114 3.4k
Marco Lorenzi France 22 389 0.7× 168 0.4× 39 0.1× 248 0.8× 355 1.1× 93 1.6k
Manuel Gómez-Río Spain 19 264 0.5× 137 0.3× 73 0.2× 115 0.4× 221 0.7× 56 1.2k
Sanjiv Bhatia United States 27 298 0.5× 165 0.4× 129 0.4× 61 0.2× 896 2.9× 110 2.2k
Kelvin Wong United States 26 567 1.0× 79 0.2× 119 0.3× 100 0.3× 109 0.3× 78 1.9k
Francesca Gallivanone Italy 21 947 1.7× 237 0.5× 32 0.1× 280 0.9× 240 0.8× 51 1.9k
F. Reed Murtagh United States 27 369 0.7× 146 0.3× 94 0.3× 667 2.1× 220 0.7× 92 3.4k

Countries citing papers authored by Xiao Da

Since Specialization
Citations

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

Fields of papers citing papers by Xiao Da

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiao Da

This figure shows the co-authorship network connecting the top 25 collaborators of Xiao Da. A scholar is included among the top collaborators of Xiao Da 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 Xiao Da. Xiao Da 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.
Da, Xiao, et al.. (2024). Spectris™ treatment preserves corpus callosum structure in Alzheimer's disease. Frontiers in Neurology. 15. 1452930–1452930. 3 indexed citations
2.
Da, Xiao, et al.. (2023). Noninvasive Gamma Sensory Stimulation May Reduce White Matter and Myelin Loss in Alzheimer’s Disease. Journal of Alzheimer s Disease. 97(1). 359–372. 18 indexed citations
3.
Lauer, Arne, Xiao Da, Christine Duncan, et al.. (2023). Hematopoietic stem-cell gene therapy is associated with restored white matter microvascular function in cerebral adrenoleukodystrophy. Nature Communications. 14(1). 1900–1900. 10 indexed citations
4.
Da, Xiao, et al.. (2022). Path context augmented statement and network for learning programs. Empirical Software Engineering. 27(2). 6 indexed citations
5.
6.
Rathore, Saima, Hamed Akbari, Spyridon Bakas, et al.. (2019). Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of de novo Glioblastoma Patients. Frontiers in Computational Neuroscience. 13. 81–81. 7 indexed citations
7.
Da, Xiao, et al.. (2018). Improving the Universality and Learnability of Neural Programmer-Interpreters with Combinator Abstraction. arXiv (Cornell University). 3 indexed citations
8.
Ou, Yangming, Lilla Zöllei, Xiao Da, et al.. (2018). Field of View Normalization in Multi-Site Brain MRI. Neuroinformatics. 16(3-4). 431–444. 21 indexed citations
9.
Da, Xiao, et al.. (2016). Provable Data Possession System for Realistic Cloud Storage Environments. 27(9). 2413. 1 indexed citations
10.
Bilello, Michel, Hamed Akbari, Xiao Da, et al.. (2016). Population-based MRI atlases of spatial distribution are specific to patient and tumor characteristics in glioblastoma. NeuroImage Clinical. 12. 34–40. 48 indexed citations
11.
Akbari, Hamed, Luke Macyszyn, Xiao Da, et al.. (2016). Imaging Surrogates of Infiltration Obtained Via Multiparametric Imaging Pattern Analysis Predict Subsequent Location of Recurrence of Glioblastoma. Neurosurgery. 78(4). 572–580. 107 indexed citations
12.
Gaonkar, Bilwaj, Luke Macyszyn, Michel Bilello, et al.. (2015). Automated Tumor Volumetry Using Computer-Aided Image Segmentation. Academic Radiology. 22(5). 653–661. 31 indexed citations
13.
Goodfellow, Ian, Mehdi Mirza, Xiao Da, Aaron Courville, & Yoshua Bengio. (2014). An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks. arXiv (Cornell University). 341 indexed citations breakdown →
14.
Toledo, Jon B., Michael W. Weiner, David A. Wolk, et al.. (2014). Neuronal injury biomarkers and prognosis in ADNI subjects with normal cognition. Acta Neuropathologica Communications. 2(1). 26–26. 63 indexed citations
15.
Akbari, Hamed, Luke Macyszyn, Xiao Da, et al.. (2014). Pattern Analysis of Dynamic Susceptibility Contrast-enhanced MR Imaging Demonstrates Peritumoral Tissue Heterogeneity. Radiology. 273(2). 502–510. 75 indexed citations
16.
Zeng, Cheng, et al.. (2013). Effective method for analysis of Cisco IOS image injection attack. 30(12). 3775–3778. 1 indexed citations
17.
Toledo, Jon B., Xiao Da, Priyanka Bhatt, et al.. (2013). Relationship between Plasma Analytes and SPARE-AD Defined Brain Atrophy Patterns in ADNI. PLoS ONE. 8(2). e55531–e55531. 35 indexed citations
18.
19.
Toledo, Jon B., Nigel J. Cairns, Xiao Da, et al.. (2013). Clinical and multimodal biomarker correlates of ADNI neuropathological findings. Acta Neuropathologica Communications. 1(1). 65–65. 136 indexed citations
20.
Da, Xiao. (2008). A case study of acquisition of ba construction in Mandarin. Suvremena lingvistika. 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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