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Basic Information

付来义

Gender: Male

Professional Title: Associate Professor

Degree: Doctor

School/Department: School of Automation Science and Engineering

Business Address: 西安市碑林区咸宁西路28号/中国西部科技创新港4号巨构

Contact Information:

Discipline: Control Science and Engineering

Enrollment disciplines: Control Science and Engineering

Personal Profile

Laiyi Fu, Ph.D. | Associate Professor | Master's Supervisor
   Selected for the Young Outstanding Talent Program (Track A), Xi'an Jiaotong University
   Institute of Systems Engineering, School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University
   Chief Scientist, Shaanxi Provincial “Scientist + Engineer” Team
   Selected for the Young Talent Support Program of the Xi'an Association for Science and Technology

 

Associate Professor, Institute of Intelligent Control and Industrial Big Data, iHarbour, Xi'an Jiaotong University & State Key Laboratory of Astronautic Dynamics
 

Researcher, Shaanxi Engineering Laboratory for Advanced Control of Robots & Shaanxi Provincial Engineering Research Center
  

Researcher, National Engineering Research Center for Visual Information and Applications
 

Researcher, Zhejiang Research Institute of Xi'an Jiaotong University
 

Specially Appointed Researcher, Sichuan Institute of Digital Economy
  

Committee Member, Biomedical Intelligent Computing Committee, Shaanxi Computer Society
  

Committee Member, Artificial Intelligence Committee, Zhejiang Society for Bioinformatics
  

Expert, Expert Pool of the Chinese Association of Automation; Committee Member, Preparatory Committee for Smart Ecology


More information can be found in my personal website

Teaching Information

Research Field

Research Interests


  • AI for biomedicine and bioinformatics: single-cell and multi-omics analysis, medical image analysis, disease-association modelling, drug-target virtual screening, and domain-specific foundation models.

  • AI for genomics and smart breeding: crop genomics, telomere-to-telomere (T2T) genome analysis, intelligent breeding, agricultural foundation models, and research platforms for smart agriculture.

  • Data-driven systems: graph learning and large-scale data modelling for complex systems, with selected applications in intelligent industry.


    I welcome enquiries from motivated undergraduate and graduate students who are interested in interdisciplinary AI4S research. Please contact me by email with a brief introduction and your CV.