Integrating Generative AI into the Research Cycle: Enhancing Discovery, Analysis and Dissemination

Generative AI is reshaping how research is conducted—from idea generation to publication. This interactive workshop explores how AI-based tools can enhance each stage of the research cycle, improving efficiency, creativity, and decision-making.
In this workshop, you will engage with cutting-edge AI applications*, including ChatGPT, DeepSeek, Claude, Perplexity.ai, you.com and GitHub Copilot to learn streamlining your research processes. Through a mix of hands-on exercises, demonstrations, and discussions, this session will equip you with practical strategies for integrating AI into your work routines while maintaining good scientific practice.

The specific learning goals and topics of the workshop are:

• From Observation to Hypothesis: Use AI to brainstorm, explore research questions and refine ideas.
• Literature Review & Knowledge Synthesis: Leverage AI-driven search engines and research tools for deeper, more efficient literature exploration.
• Proposal & Manuscript Writing: Employ AI as a writing assistant for structuring proposals, refining arguments, and improving clarity.
• Experimentation & Data Handling: Explore AI to structure data, assisting in survey analysis, and supporting decision-making.
• AI for Coding & Computational Research: Enhance programming skills with AI-based copilots, whether for refining existing workflows or starting from scratch.
• Publishing & Science Communication: Utilize AI to craft compelling narratives for peer-reviewed publications and public engagement.
• Ethical Considerations & Responsible AI Use: Discuss the challenges of AI in research, including bias, hallucinations, and data privacy, within the framework of Good Scientific Practice.