At the recent EC2U Workshop on “AI Tools in Scientific Research”, over 350 Ph.D. students from across Europe gathered to explore how artificial intelligence can transform the research process. One of the highlights of the event was the presentation “From Search to Synthesis: Supercharging Your Ph.D. Literature Survey with AI”, presented by Eugénio Rodrigues, which demonstrated a practical, step-by-step approach to integrating AI into literature survey workflows.
The session introduced a method that begins with a broad academic search—using databases such as Scopus—and a small, representative set of abstracts. Participants learned how to import these abstracts into NotebookLM to identify recurring themes, terminology, and patterns that signal irrelevant results. The AI’s analytical capability allowed researchers to refine their search queries iteratively, applying more precise keywords and Boolean operators to enhance both the specificity and efficiency of their literature retrieval.
The second part of the workshop showcased how AI can support synthesis and structuring. Using a curated set of relevant abstracts, NotebookLM was employed to generate outlines and group them thematically. This approach not only streamlines the literature survey process but also helps young researchers identify the importance and urgency of their topic.