Assoc. Prof. Dr Duantengchuan Li, School of Information Management, Wuhan University, Wuhan, China, Cahina
Assoc. Prof. Dr. Duantengchuan Li is a distinguished researcher at the School of Information Management, Wuhan University, China 🎓. His expertise spans Recommender Systems, Knowledge Graphs, Reinforcement Learning, Autonomous Driving, Large Language Models, and Computer Vision 🤖📊. With 40+ publications in top-tier journals and conferences such as IEEE TKDE, ACM TWEB, and AAAI đź“ś, Dr. Li has earned over 800 citations on Google Scholar 🌍. He has served as a Guest Editor for Electronics and a reviewer for premier journals, including IEEE TNNLS, IEEE TII, and Information Sciences đź“ť. Dr. Li’s impactful research contributions in AI and machine learning make him a leading expert in the field 🚀. His achievements include multiple national and provincial scholarships and a Bronze Medal in the “Internet+” Competition 🏅. His commitment to advancing AI-driven solutions for real-world applications makes him a strong candidate for the Best Researcher Award 🌟.
Publication Profile
Google Scholar
Education
Dr. Duantengchuan Li holds a Ph.D. in Computer Science from Wuhan University, China 🎓, where he specialized in AI-driven Recommender Systems and Knowledge Graphs 🤖📊. Prior to his Ph.D., he earned a Master’s degree from the Faculty of Artificial Intelligence in Education, Central China Normal University 🏫. His academic journey began with a Bachelor’s degree in Computer Science, where he honed his skills in machine learning, deep learning, and computational intelligence 💻. Throughout his education, he actively engaged in cutting-edge research and contributed to high-impact publications 📜. His strong academic foundation has paved the way for groundbreaking work in large-scale AI applications and intelligent systems 🚀. With an outstanding academic record and multiple scholarships, Dr. Li has established himself as a leading AI researcher, dedicated to advancing computational intelligence, knowledge-based systems, and deep learning architectures 🏆.
Experience
Dr. Duantengchuan Li is currently an Associate Researcher at the School of Information Management, Wuhan University, China 🏫. He has extensive experience in artificial intelligence, knowledge graphs, recommender systems, and deep learning 🤖. Dr. Li has been actively involved in academic publishing, serving as a Guest Editor for Electronics and as a reviewer for prestigious journals like IEEE TKDE, ACM TKDD, and IEEE TNNLS 📝. His research has been featured in top CCF A & B-ranked journals and conferences, including AAAI, ICWS, CAiSE, and IEEE Transactions 📊. Before joining Wuhan University, he completed his Ph.D. in Computer Science, contributing to AI-driven recommendation models 💡. His expertise extends to autonomous driving, reinforcement learning, and computer vision, and he continues to mentor young researchers in AI applications 🚀. His contributions in intelligent computing and AI research have made him a leading figure in his field 🌍.
Awards & Honors
Dr. Duantengchuan Li has received numerous accolades for his contributions to AI and computer science 🏆. In 2023, he led a team to win the Bronze Award in the prestigious “Internet+” Competition 🏅. His academic excellence was recognized with the National Scholarship (2019) 🎓 and the Provincial Outstanding Graduate Award (2017) 🏅. Additionally, he was honored with the Provincial Government Scholarship (2015) for his outstanding performance in research and academics đź“ś. Dr. Li also holds a Network Engineer Qualification Certification (2016), further demonstrating his technical expertise đź’». His contributions in AI research, particularly in deep learning, recommender systems, and autonomous driving, have earned him a spot among China’s top researchers 🚀. With 40+ high-impact publications and 800+ citations, Dr. Li’s work continues to shape the future of artificial intelligence and machine learning 🌟.
Research Focus
Dr. Duantengchuan Li’s research primarily focuses on Recommender Systems, Knowledge Graphs, Reinforcement Learning, Large Language Models, Autonomous Driving, and Computer Vision 🤖📊. His work explores efficient AI-driven recommendations, leveraging graph neural networks, deep learning, and sequential modeling to improve information retrieval đź“ś. He has also contributed to structured output evaluation for Large Language Models (LLMs), optimizing their prompt engineering and reasoning capabilities đź’ˇ. In autonomous driving, his research enhances intelligent vehicle navigation using deep reinforcement learning đźš—. Additionally, he has developed advanced cold-start QoS prediction models and multi-relation modeling for personalized recommendations 🔍. His work has been published in IEEE TKDE, ACM TOSEM, AAAI, and Information Sciences, demonstrating his cutting-edge innovations in AI applications 🚀. By integrating machine learning, knowledge graphs, and neural networks, Dr. Li continues to advance intelligent computing solutions for real-world problems 🌍.
Publication Top Notes
MFDNet: Collaborative poses perception and matrix Fisher distribution for head pose estimation
EDMF: Efficient deep matrix factorization with review feature learning for industrial recommender system
Multi-perspective social recommendation method with graph representation learning
CARM: Confidence-aware recommender model via review representation learning and historical rating behavior in the online platforms
Knowledge graph representation learning with simplifying hierarchical feature propagation
Knowledge graph representation learning with simplifying hierarchical feature propagation
Precise head pose estimation on HPD5A database for attention recognition based on convolutional neural network in human-computer interaction
Integrating user short-term intentions and long-term preferences in heterogeneous hypergraph networks for sequential recommendation