Xi Chen
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Staff Fellow
Also affiliated: Qingdao University (2025); University of Southern California (2023); University of Maryland, Baltimore (2008); United States Food and Drug Administration (2021–2026); University of Illinois Urbana-Champaign (2022); Sun Yat-sen University (2019); Lingnan University (2024); State Grid Corporation of China (China) (2018); Shanxi Medical University (2023); Beijing University of Chinese Medicine (2015–2022); University of Strathclyde (2023); Dalian Medical University (2020); Chinese Academy of Sciences (2016–2022); Vanderbilt University (2015); Washington University in St. Louis (2008); University of Michigan (2021); State Administration of Traditional Chinese Medicine of the People's Republic of China (2020); Wuhan University (2021–2023); Center for Excellence in Brain Science and Intelligence Technology (2016); Institute of Automation (2016–2022); Children's Hospital of Zhejiang University (2017–2018); First Affiliated Hospital of Dalian Medical University (2020); Flatiron Institute (2023); University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center (2008); State Key Laboratory of Industrial Control Technology (2022); Shanghai Ocean University (2020); Imperial College London (2023); Carnegie Mellon University (2011); Zhejiang University (2013–2025); Miami University (2013–2014); Stanford University (2017)
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Xi Chen's research focuses on the application of artificial intelligence and computational methods to drug discovery and toxicology. Chen has investigated the use of transfer learning for protein representation and developed generative adversarial networks (GANs) as alternatives to animal studies for toxicological assessments, as demonstrated by the Tox-GAN model. Other work includes multi-constraint molecular generation using transformer models, knowledge distillation, and reinforcement learning, as well as predicting drug response using molecular representations. Chen also has a publication on identifying human DNA ligase inhibitors through computer-aided drug design.
With an h-index of 19, 65 total publications, and over 1,900 citations, Chen's scholarship metrics indicate significant contributions to the field. Recent work highlights a continued focus on AI-driven approaches in medical research, including the development of AI-based language models for drug discovery and development, and generative adversarial network models for clinical pathology assessment.
Metrics
- h-index: 19
- Publications: 65
- Citations: 1,951
Positions
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Staff Fellow 2022–presentNational Center for Toxicological Research Division of Bioinformatics and Biostatistics ORCID
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Postdoctoral Fellow 2020–2022National Center for Toxicological Research Division of Bioinformatics and Biostatistics ORCID
Selected Publications
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GanCtrl: a generative AI approach to derive study-aligned synthetic controls for reducing concurrent control animal use (2026)
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Bridging organ transcriptomics for advancing multiple organ toxicity assessment with a generative AI approach (2024)
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A generative adversarial network model alternative to animal studies for clinical pathology assessment (2023)
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AnimalGAN: A Generative Adversarial Network Model Alternative to Animal Studies for Clinical Pathology Assessment (2023)
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Tox-GAN: An Artificial Intelligence Approach Alternative to Animal Studies—A Case Study With Toxicogenomics (2021)
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DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction (2021)
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AI-based language models powering drug discovery and development (2021)
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Unraveling Gene Fusions for Drug Repositioning in High-Risk Neuroblastoma (2021)
Collaboration Network
Top Collaborators
- AI-based language models powering drug discovery and development
- Tox-GAN: An Artificial Intelligence Approach Alternative to Animal Studies—A Case Study With Toxicogenomics
- A generative adversarial network model alternative to animal studies for clinical pathology assessment
- Bridging organ transcriptomics for advancing multiple organ toxicity assessment with a generative AI approach
- DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction
Showing 5 of 8 shared publications
- AI-based language models powering drug discovery and development
- Tox-GAN: An Artificial Intelligence Approach Alternative to Animal Studies—A Case Study With Toxicogenomics
- A generative adversarial network model alternative to animal studies for clinical pathology assessment
- DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction
- Unraveling Gene Fusions for Drug Repositioning in High-Risk Neuroblastoma
Showing 5 of 6 shared publications
- Bridging organ transcriptomics for advancing multiple organ toxicity assessment with a generative AI approach
- DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction
- GanCtrl: a generative AI approach to derive study-aligned synthetic controls for reducing concurrent control animal use
- AI-based language models powering drug discovery and development
- Unraveling Gene Fusions for Drug Repositioning in High-Risk Neuroblastoma
- DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction
- Unraveling Gene Fusions for Drug Repositioning in High-Risk Neuroblastoma
- AI-based language models powering drug discovery and development
- A generative adversarial network model alternative to animal studies for clinical pathology assessment
- Unraveling Gene Fusions for Drug Repositioning in High-Risk Neuroblastoma
- AI-based language models powering drug discovery and development
- DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction
- DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction
- DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction
- DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction
- Tox-GAN: An Artificial Intelligence Approach Alternative to Animal Studies—A Case Study With Toxicogenomics
- AnimalGAN: A Generative Adversarial Network Model Alternative to Animal Studies for Clinical Pathology Assessment
- GanCtrl: a generative AI approach to derive study-aligned synthetic controls for reducing concurrent control animal use
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