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D-Index & Metrics

Computer Science

D-Index
93
Citations
33639
World Ranking
516
National Ranking
275

Overview

Jimeng Sun is a researcher affiliated with the University of Illinois at Urbana-Champaign in the United States. Their work primarily spans the fields of Computer Science and Medicine, with a significant focus on Artificial Intelligence and its applications across various domains.

Their scholarly contributions cover multiple subfields including:

  • Artificial Intelligence
  • Molecular Biology
  • Computational Theory and Mathematics
  • Radiology, Nuclear Medicine and Imaging
  • Materials Chemistry

Jimeng Sun's research topics emphasize:

  • Machine Learning in Healthcare
  • Topic Modeling
  • Computational Drug Discovery Methods
  • Biomedical Text Mining and Ontologies
  • Machine Learning in Materials Science
  • Artificial Intelligence in Healthcare and Education
  • Artificial Intelligence in Healthcare

Their recent published papers include:

  • Scientific discovery in the age of artificial intelligence (2023), published in Nature
  • MolTrans: Molecular Interaction Transformer for drug-target interaction prediction (2020), published in Bioinformatics
  • Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review (2020), published in Computers in Biology and Medicine
  • DeepPurpose: a deep learning library for drug-target interaction prediction (2020), published in Bioinformatics
  • Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States (2022), published in Proceedings of the National Academy of Sciences

Jimeng Sun frequently collaborates with other researchers, including:

  • Cao Xiao
  • Lucas M. Glass
  • Tianfan Fu
  • Brandon Theodorou
  • Zifeng Wang

Their work has been published extensively in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of the American Medical Informatics Association
  • Patterns

Best Publications

  • Social influence analysis in large-scale networks

    Jie Tang;Jimeng Sun;Chi Wang;Zi Yang

  • Doctor AI: Predicting Clinical Events via Recurrent Neural Networks

    Edward Choi;Mohammad Taha Bahadori;Andy Schuetz;Walter F. Stewart

  • RETAIN: An interpretable predictive model for healthcare using reverse time attention mechanism

    Edward Choi;Mohammad Taha Bahadori;Jimeng Sun;Joshua Kulas

  • Using recurrent neural network models for early detection of heart failure onset.

    Edward Choi;Andy Schuetz;Walter F Stewart;Jimeng Sun

  • Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review.

    Cao Xiao;Edward Choi;Jimeng Sun

  • The TPR*-tree: an optimized spatio-temporal access method for predictive queries

    Yufei Tao;Dimitris Papadias;Jimeng Sun

  • GRAM: Graph-based Attention Model for Healthcare Representation Learning

    Edward Choi;Mohammad Taha Bahadori;Le Song;Walter F. Stewart

  • GraphScope: parameter-free mining of large time-evolving graphs

    Jimeng Sun;Christos Faloutsos;Spiros Papadimitriou;Philip S. Yu

  • Beyond streams and graphs: dynamic tensor analysis

    Jimeng Sun;Dacheng Tao;Christos Faloutsos

  • Streaming pattern discovery in multiple time-series

    Spiros Papadimitriou;Jimeng Sun;Christos Faloutsos

  • Multi-layer Representation Learning for Medical Concepts

    Edward Choi;Mohammad Taha Bahadori;Elizabeth Searles;Catherine Coffey

  • Explainable Prediction of Medical Codes from Clinical Text

    James Mullenbach;Sarah Wiegreffe;Jon Duke;Jimeng Sun

  • MolTrans: Molecular interaction transformer for drug target interaction prediction

    Kexin Huang;Cao Xiao;Lucas M Glass;Jimeng Sun

  • Temporal recommendation on graphs via long- and short-term preference fusion

    Liang Xiang;Quan Yuan;Shiwan Zhao;Li Chen

  • Scalable Tensor Decompositions for Multi-aspect Data Mining

    T.G. Kolda;Jimeng Sun

  • Generating Multi-label Discrete Patient Records using Generative Adversarial Networks

    Edward Choi;Siddharth Biswal;Bradley A. Malin;Jon Duke

  • Neighborhood formation and anomaly detection in bipartite graphs

    Jimeng Sun;Huiming Qu;D. Chakrabarti;C. Faloutsos

  • From hype to reality: data science enabling personalized medicine

    Holger Fröhlich;Rudi Balling;Niko Beerenwinkel;Oliver Kohlbacher

  • Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review.

    Shenda Hong;Yuxi Zhou;Junyuan Shang;Cao Xiao

  • Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

    Ee-Peng Lim;Marianne Winslett;Mark Sanderson;Ada Fu

  • Cross-domain collaboration recommendation

    Jie Tang;Sen Wu;Jimeng Sun;Hang Su

  • RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism

    Edward Choi;Mohammad Taha Bahadori;Joshua A. Kulas;Andy Schuetz

  • SUSTain: Scalable Unsupervised Scoring for Tensors and its Application to Phenotyping

    Ioakeim Perros;Evangelos E. Papalexakis;Haesun Park;Richard Vuduc

Frequent Co-Authors

Cao Xiao
Cao Xiao General Electric (United Kingdom)
Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
Bradley A. Malin
Bradley A. Malin Vanderbilt University Medical Center
Robert Chen
Robert Chen University Health Network
M. Brandon Westover
M. Brandon Westover Harvard University
Richard Vuduc
Richard Vuduc Georgia Institute of Technology
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Jie Tang
Jie Tang Tsinghua University
Joydeep Ghosh
Joydeep Ghosh The University of Texas at Austin
Yufei Tao
Yufei Tao Chinese University of Hong Kong

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