Pengjie Ren

Pengjie Ren is an academic lecturer specializing in information retrieval, recommendation systems, and conversational AI. He holds teaching roles in courses such as Introduction to Big Data Processing Technology, Probability Theory and Mathematical Statistics, Ph.D Professional English, and Statistical Natural Language Processing. As a supervisor, he has guided both PhD and Master's students in research-oriented projects.

His research focuses on advancing conversational systems, generative models, and reinforcement learning applications in recommendation systems. He has contributed to top conferences like SIGIR, WWW, AAAI, and ACL, with notable work on knowledge-grounded dialogues, sequential recommenders, and debiasing techniques in AI.

Pengjie actively serves the academic community as an organizing committee member (NLPCC 2021, YSSNLP 2021) and workshop co-chair (SIGIR AIIS 2020, WSDM NLP4REC 2020). He is also a program committee member for major conferences and a reviewer for journals like TOIS, TKDE, and IPM.

His teaching and research emphasize practical applications of AI in dialogue systems, privacy-aware recommendation, and multi-domain learning, with a focus on bridging theory and real-world implementation.