Jinpeng Chen | recommendation systems | Best Researcher Award

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Assoc Prof Dr. Jinpeng Chen | recommendation systems | Best Researcher Award

Beijing University of Posts & Telecommunications | China

Publication Profile

Google Scholar

Biography of Assoc Prof Dr. Jinpeng Chen 👨‍💻

🎓 Education & Global Experience

Assoc. Prof. Dr. Jinpeng Chen began his academic journey with a Ph.D. in Computer Science from Beihang University (2011–2016). During his doctoral studies, he expanded his research horizons internationally—spending a year as a Visiting Ph.D. scholar at Aalborg University in Denmark (2014–2015), and also working as a Research Assistant at the University of Sydney in Australia (2013–2014). These global experiences laid the foundation for his collaborative and cross-cultural approach to research. 🌍📘

👨‍🏫 Academic Positions

Dr. Chen currently serves as an Associate Professor at the Beijing University of Posts and Telecommunications (BUPT), a position he has held since December 2018. Prior to that, he was an Assistant Professor at BUPT from 2016 to 2018. Over the years, he has been actively involved in teaching, mentoring graduate students, and leading innovative research projects. 🏫🔬

🔬 Research Interests & Projects

His research primarily focuses on Data Mining, Social Network Analysis, Crowdsourcing-based Data Processing, Machine Learning, and Artificial Intelligence. Dr. Chen has led and contributed to numerous high-impact research projects, including the Beijing Natural Science Foundation (2023–2026) and multiple grants from the National Natural Science Foundation of China. He also participated in the National Key R&D Program of China, contributing to the development of algorithms for user profiling, recommendations, traffic analysis, and intelligent marketing. 📊🤖

🧠 Academic Service & Community Contribution

Dr. Chen is a dedicated member of the global research community. He has served as a reviewer for prestigious journals such as ACM TOIS, TKDD, IEEE TNNLS, IEEE TFS, and TCC, among others. He is also a frequent external reviewer and program committee member for leading conferences like KDD, WWW, DASFAA, IJCAI, and BigData. His expert insights and evaluations have helped maintain the high standards of academic publishing. 📝🌐

🎤 Talks & Presentations

As a recognized thought leader in his field, Dr. Chen has been invited to speak at major academic events. Notable presentations include his talk at the KDD China 2023 Summer School on “Mandari: Multi-Modal Temporal Knowledge Graph-aware Sub-graph Embedding”, and his keynote at ICAIBD 2023 on “Sequential Intention-aware Recommender based on User Interaction Graph”. He has also shared his research at CGCM 2014 and during a special invitation to the School of Information Technologies at the University of Sydney. 🗣️📢

🚀 Impact & Vision

Assoc. Prof. Dr. Jinpeng Chen continues to drive innovation at the intersection of data science and artificial intelligence. His research not only contributes to academic advancement but also influences real-world applications in technology, business, and social platforms. With a passion for AI and a strong foundation in collaborative research, he is shaping the future of intelligent systems, one algorithm at a time. 🌟📈

📚 Top Notes Publications

Title: Automatic tagging by leveraging visual and annotated features in social media

Authors: J. Chen, P. Ying, X. Fu, X. Luo, H. Guan, K. Wei
Journal: IEEE Transactions on Multimedia
Year: 2021

Title: Inferring tag co-occurrence relationship across heterogeneous social networks

Authors: J. Chen, Y. Liu, G. Yang, M. Zou
Journal: Applied Soft Computing
Year: 2018

Title: Sequential intention-aware recommender based on user interaction graph

Authors: J. Chen, Y. Cao, F. Zhang, P. Sun, K. Wei
Journal: Proceedings of the 2022 International Conference on Multimedia Retrieval
Year: 2022

Title: From tie strength to function: Home location estimation in social network

Authors: J. Chen, Y. Liu, M. Zou
Journal: 2014 IEEE Computers, Communications and IT Applications Conference
Year: 2014

Title: FePN: A robust feature purification network to defend against adversarial examples

Authors: D. Cao, K. Wei, Y. Wu, J. Zhang, B. Feng, J. Chen
Journal: Computers & Security
Year: 2023

Sogand Dehghan | social network analysis | Best Innovation Award

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Ms. Sogand Dehghan | social network analysis | Best Innovation Award

Ms. Sogand Dehghan at K. N. Toosi University of Technology, Iran

👨‍🎓Professional Profiles

Orcid Profile

Google Scholar  Profile

👩‍💻 Summary

Ms. Sogand Dehghan an Information Technology specialist with expertise in data analysis and software development. My work primarily focuses on collecting, cleaning, and analyzing data from various sources to create actionable reports and dashboards for organizational decision-making. I am passionate about using data-driven strategies to help businesses achieve their goals, with a particular interest in social media analysis and its alignment with organizational objectives. Additionally, I enjoy developing data-driven software solutions that enhance operational efficiency.

🎓 Education

Ms. Sogand Dehghan earned my Master’s Degree in Information Technology from K.N. Toosi University of Technology (2019-2022) and my Bachelor’s Degree in Information Technology with a grade of 97% from Payame Noor University (2012-2016). My thesis, titled “Provision of an Efficient Model for Evaluation of Social Media Users Using Machine Learning Techniques,” focused on leveraging machine learning to assess social media engagement and user behavior.

💼 Professional Experience

Ms. Sogand Dehghan currently hold two key roles: as an Instructor at National Skills University, where I teach courses on Advanced Programming and Data Analysis (since Sep 2024), and as a Data Analyst at GAM Arak Industry, where I focus on data mining, machine learning, and visualizing data insights using tools like Power BI, Python, SQL Server, and SSRS (since Jan 2024). Additionally, I serve as a Software Developer at GAM Arak Industry, working with C#, ASP.NET Core, and SQL Server to build scalable software solutions (since Apr 2023). In my previous role at Kherad Sanat Arvand (Apr 2022 – Jun 2023), I honed my skills in data analysis and dashboard development.

📚 Academic Citations

My research has been published in prestigious journals. My paper, “The Credibility Assessment of Twitter Users Based on Organizational Objectives,” was published in Computers in Human Behavior (Sep 2024), where I developed a model for assessing the credibility of Twitter users by integrating profile data with academic sources like Google Scholar. Another notable publication, “The Evaluation of Social Media Users’ Credibility in Big Data Life Cycle,” appeared in the Journal of Information and Communication Technology (Sep 2023), in which I reviewed existing frameworks for evaluating social media user credibility.

🔧 Technical Skills

My technical skill set includes expertise in C#, ASP.NET, Python, and SQL Server for software development. I specialize in Data Visualization with Power BI, Data Mining, Machine Learning, and Social Network Analysis. Additionally, I have a solid foundation in Text Mining and Data Modeling, which enables me to provide comprehensive solutions for data-driven challenges in various organizational contexts.

👨‍🏫 Teaching Experience

As an Instructor at National Skills University, I teach Advanced Programming and Data Analysis. I focus on equipping students with the skills needed to thrive in the data-driven world of technology. My approach integrates real-world data problems with theoretical knowledge to help students apply their learning in practical scenarios.

🔍 Research Interests

My research interests lie in the intersection of Machine Learning and Social Network Analysis. I am particularly interested in developing models to evaluate social media user credibility, integrating heterogeneous data sources for organizational decision-making, and exploring the broader implications of big data in evaluating trust and influence within social networks.