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Hui Han

Hui Han

Postdoktor
Institutt for datateknologi og informatikk

hui.han@ntnu.no
IT-bygget, 160, Gløshaugen
Google Scholar Personal Website
Om Forskning Publikasjoner

Om

Dr. Hui HAN is a postdoctoral research fellow at the Department of Computer Science. She received her PhD. in Industrial Engineering from the Technical University of Madrid (UPM). Then she was a postdoctoral researcher at the Data Science department of Fraunhofer IESE, Germany. Her research focus is data science (specifically on Edge AI and TinyML (Tiny Machine Learning) ). She also leads research initiatives on the design of sustainability modeling for reverse logistics and closed-loop supply chains, and offers expertise in the areas of social commerce and Industry 4.0. Dr. Han has published 11 journal papers and 3 conference papers as the first author with 504 citations. Her articles have appeared in such journals as Technological Forecasting & Social Change, Electronic Commerce Research and Applications, Journal of Theoretical and Applied Electronic Commerce Research, and Expert Systems with Applications. Her teaching includes Auditing, Brand Management, and Management Information Systems.

Current Service and Affiliation

Guest Editor, Metaverse Special Issue for Service Business: An International Journal.

Call for papers for the Metaverse Special Issue from Service Business: An International Journal (IF 5.236) 

WorkVitenskapelig, faglig og kunstnerisk arbeid

Hui Han and Silvana Trimi (2022). Towards a data science platform for improving SME collaboration through Industry 4.0 technologies. Technological Forecasting and Social Change, 174, 1-13. DOI: https://doi.org/10.1016/j.techfore.2021.121242

Hui Han and Jingyue Li (2022). Tiny Machine Learning: A New Technique for AI Security. ERCIM NEWS 129, 16-17

Hui Han, HongYi Xu, and HongQuan Chen (2018). Social commerce: A systematic review and data synthesis. Electronic Commerce Research and Applications, 30(2018), 38–50. DOI: https://doi.org/10.1016/j.elerap.2018.05.005.

Hui Han and Silvana Trimi (2018). A Fuzzy TOPSIS Method for Performance Evaluation of Reverse Logistics in Social Commerce Platforms. Expert Systems with Applications, 103(2018), 133-145. DOI: https://doi.org/10.1016/j.eswa.2018.03.003

Hui Han and Silvana Trimi (2017). Social commerce design: a framework and application. Journal of Theoretical and Applied Electronic Commerce Research, 12(3), 50-68. DOI:4067/S0718-18762017000300005

Hui Han and Eva Ponce-Cueto (2015). Waste Collection Vehicle Routing Problem: A Literature Review. PROMET – Traffic & Transportation, 27(4), 345–358. DOI: 10.7307/ptt.v27i4.1616

Kompetanseord

  • Edge AI
  • Industry 4.0
  • Multicriteria Decision Analysis
  • Social commerce
  • Sustainable supply chain
  • Tiny Machine Learning

Forskning

Research Interests

  • Data Science: Edge AI and TinyML (Tiny Machine Learning)
  • Industry 4.0
  • Multicriteria Decision Analysis: Fuzzy TOPSIS
  • Information System: Social commerce and e-commerce
  • Sustainability: Reverse logistics and closed-loop supply chains

Research Experience

  • RISE, Sweden (Jan 2023)
  • Fraunhofer IESE, Germany (2021)
  • University of Jyväskylä, Finland (2013)
  • JAMK University of Applied Science, Finland (2011)

Publikasjoner

Towards a data science platform for improving SME collaboration through Industry 4.0 technologies

Hui Han and Silvana Trimi (2022). Towards a data science platform for improving SME collaboration through Industry 4.0 technologies. Technological Forecasting and Social Change, 174, 1-13. DOI: https://doi.org/10.1016/j.techfore.2021.121242

Social commerce: A systematic review and data synthesis

Hui Han, HongYi Xu and HongQuan Chen (2018). Social commerce: A systematic review and data synthesis. Electronic Commerce Research and Applications, 30(2018), 38–50. DOI: https://doi.org/10.1016/j.elerap.2018.05.005.

A Fuzzy TOPSIS Method for Performance Evaluation of Reverse Logistics in Social Commerce Platforms

Hui Han and Silvana Trimi (2018). A Fuzzy TOPSIS Method for Performance Evaluation of Reverse Logistics in Social Commerce Platforms. Expert Systems with Applications, 103(2018), 133-145. DOI: https://doi.org/10.1016/j.eswa.2018.03.003
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