Xingqiao Wang
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Also affiliated: Shenyang Ligong University (2015–2019); Jilin University (1989–2019); Tiangong University (2023); Chinese Academy of Sciences (2010); Changchun Institute of Applied Chemistry (2010); State Key Laboratory of Electroanalytical Chemistry (2010); East China Normal University (2012); Xi'an Jiaotong University (2019); Tsinghua University (2011)
Research Areas
Biomedical Subjects
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Biography and Research Information
OverviewAI-generated summary
Xingqiao Wang's research focuses on the development and application of advanced algorithms and computational frameworks, particularly in the areas of artificial intelligence and machine learning. Wang has investigated methods for traffic congestion prediction, employing temporal association rules mining. Further work has explored optimization algorithms for wireless sensor networks, such as a Virtual Force Algorithm-Lévy-Embedded Grey Wolf Optimization Algorithm. In the health sciences, Wang has contributed to pharmacovigilance through the development of AI-powered causal inference frameworks like InferBERT and DeepCausality, which utilize transformer-based architectures and natural language processing to analyze free text data for drug safety. Collaborations include work with John R. Talburt and Vivek Gunasekaran at the University of Arkansas at Little Rock, and Weida Tong at the National Center for Toxicological Research.
Metrics
- h-index: 9
- Publications: 43
- Citations: 336
Selected Publications
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ARISE: Agentic Rubric-Guided Iterative Survey Engine for Automated Scholarly Paper Generation (2026)
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OmniMatch: A Large Language Model-Based Data Linkage Tool (2024)
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Train Once, Match Everywhere: Harnessing Generative Language Models for Entity Matching (2023)
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Bidirectional Encoder Representations from Transformers-like large language models in patient safety and pharmacovigilance: A comprehensive assessment of causal inference implications (2023)
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DeepCausality: A general AI-powered causal inference framework for free text: A case study of LiverTox (2022)
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InferBERT: A Transformer-Based Causal Inference Framework for Enhancing Pharmacovigilance (2021)
Collaboration Network
Top Collaborators
- InferBERT: A Transformer-Based Causal Inference Framework for Enhancing Pharmacovigilance
- DeepCausality: A general AI-powered causal inference framework for free text: A case study of LiverTox
- Bidirectional Encoder Representations from Transformers-like large language models in patient safety and pharmacovigilance: A comprehensive assessment of causal inference implications
- Bidirectional Encoder Representations from Transformers-like large language models in patient safety and pharmacovigilance: A comprehensive assessment of causal inference implications
- Train Once, Match Everywhere: Harnessing Generative Language Models for Entity Matching
- OmniMatch: A Large Language Model-Based Data Linkage Tool
- InferBERT: A Transformer-Based Causal Inference Framework for Enhancing Pharmacovigilance
- DeepCausality: A general AI-powered causal inference framework for free text: A case study of LiverTox
- InferBERT: A Transformer-Based Causal Inference Framework for Enhancing Pharmacovigilance
- InferBERT: A Transformer-Based Causal Inference Framework for Enhancing Pharmacovigilance
- DeepCausality: A general AI-powered causal inference framework for free text: A case study of LiverTox
- DeepCausality: A general AI-powered causal inference framework for free text: A case study of LiverTox
- Bidirectional Encoder Representations from Transformers-like large language models in patient safety and pharmacovigilance: A comprehensive assessment of causal inference implications
- Train Once, Match Everywhere: Harnessing Generative Language Models for Entity Matching
- Train Once, Match Everywhere: Harnessing Generative Language Models for Entity Matching
- OmniMatch: A Large Language Model-Based Data Linkage Tool
- OmniMatch: A Large Language Model-Based Data Linkage Tool
- OmniMatch: A Large Language Model-Based Data Linkage Tool
- ARISE: Agentic Rubric-Guided Iterative Survey Engine for Automated Scholarly Paper Generation
- ARISE: Agentic Rubric-Guided Iterative Survey Engine for Automated Scholarly Paper Generation
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