Jennifer Nguyen

Jennifer Nguyen is a researcher at the Department of Operations, Innovation and Data Sciences, Esade School of Business Administration and Management, Ramon Llull University. She is affiliated with the Institute for Data-Driven Decisions and has an ORCID iD (0000-0002-7498-7536). Her work focuses on data science and artificial intelligence applications in decision-making and collaborative innovation.

• University: Ramon Llull University
• School: Esade School of Business Administration and Management
• Department: Operations, Innovation and Data Sciences

Jennifer Nguyen's research interests primarily revolve around Artificial Intelligence, Natural Language Processing, and Open Innovation. She has extensively worked on Recommender Systems and Qualitative Reasoning models, integrating Fuzzy Linguistic Term Sets and Multi-Criteria Decision Making frameworks to enhance collaborative processes and knowledge generation.

Her recent publications highlight trends in AI-driven Malpractice Detection and Media Coverage Analysis. The 2025 article on European media coverage of the Israel–Gaza war employs Hesitant Fuzzy Linguistic Term Sets for comparative cross-national analysis, while her 2024 work on health sector malpractices explores Deep Attention Mechanisms and Multiple Instance Learning. Earlier research (2014–2016) focused on optimizing Reviewer Assignment and Expertise Dimensions in collaborative innovation contexts.

Jennifer Nguyen actively participates in multi-year research projects funded by both internal grants and external agencies like AGAUR. The 2017–2021 project JUICE examined Judgment and Decisions in Marketplaces, while her current 2022–2025 project investigates Natural Language Processing for Emotion Detection through fuzzy linguistic analysis.

As a member of the Institute for Data-Driven Decisions, she collaborates with international researchers across disciplines like Computer Science, Environmental Science, and Health Informatics. Her work has been cited in Scopus and referenced in academic platforms like Wikipedia and Mendeley.