About Me
Hi, I'm Linduo Li, a Master's student in Artificial Intelligence, Systems and Data (IASD) at Université Paris Sciences et Lettres (PSL).
My research interests are mainly in natural language processing and computer vision, with a broader interest in building multimodal applications for domain-specific problems. I am interested in identifying niche areas where AI systems can address concrete pain points, and in designing practical workflows that connect AI methods with real-world use cases.
Recently, I have worked on information retrieval for tax law , studying how retrieval systems can identify relevant legal authorities from complex, goal-oriented queries. I have also worked on archaeological site detection and recognition , combining computer vision, remote sensing imagery, geospatial data, and domain knowledge to support AI-assisted site discovery. I am also building AI Blazers , an open reading atlas that traces the evolution of AI through landmark research papers, exploring not only their technical contributions but also the historical context behind the ideas that shaped the field.
Previously, I worked as a Data Scientist at Blend360, where I developed machine learning models for clients in the retail industry, addressing challenges such as customer retention, attribution analysis, and data-driven decision support. I later worked as a Large Language Model Developer and AI Engineer at Boston Listener, focusing on LLM-powered applications. These experiences shaped my interest in both research-oriented machine learning and practical, deployable AI systems.