Mr. Xin Wen, Harbin Institute of Technology, China
📘 Xin Wen is currently a Master’s student in Business Administration at the Harbin Institute of Technology, focusing on Advanced Statistics and Decision Theory (2023-2025). He holds a Bachelor’s degree in Information Management from Nanjing Tech University (2019-2023). 🌍 His research includes sustainable city assessment in Shandong and food safety risk prediction, with publications in high-impact journals. Xin’s professional experience spans marketing at Amer Sports and data analysis at BSH Home Appliances. He is an award-winning participant in various academic competitions. 💻 Skills: Python, Tableau, SPSS. 🎿 Interests: Skiing, rock climbing, and video creation with 257k+ plays.
Publication profile
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📚 Education
Wen Xin is currently pursuing a Master’s degree in Business Administration at Harbin Institute of Technology (2023-2025), specializing in advanced statistical methods and decision-making theories. He previously earned a Bachelor’s degree in Information Management from Nanjing Tech University (2019-2023), where he studied data analysis, systems engineering, and data visualization.
🧪 Academic Experience
Wen is engaged in an integrated city sustainability assessment study in Shandong, utilizing deep learning and multi-criteria decision-making. He has developed models using LSTM and GCN and contributed to a paper published in Sustainable Cities and Society. He also participated in a national key R&D project focusing on food safety risk prediction, publishing his findings in Foods.
🏆 Awards
Wen’s excellence is reflected in his awards, including First Prize in the Global Brand Planning Competition in Singapore and top honors in data analysis and mathematics competitions in China.
Research Focus
Xin Wen is a researcher whose work spans multiple domains, focusing particularly on sustainability and food safety. Their research on sustainability is exemplified by the recent study on city sustainability assessment using multicriteria decision-making and deep learning methodologies. This approach integrates advanced AI techniques with environmental science to evaluate urban sustainability comprehensively 🌆♻️. Additionally, Xin Wen has contributed to food safety research, employing ensemble deep learning for predicting food safety risks, specifically concerning heavy metals in grain processing 🌾⚖️. This indicates a dual focus on leveraging technology to enhance environmental sustainability and food security, crucial areas for global health and sustainability 🌍🔬.
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