The rapid advancement of generative AI technologies has significantly transformed the landscape of academic research. This lecture aims to provide a comprehensive overview of how researchers can strategically incorporate AI tools throughout the entire research process—from ideation and literature review to writing, data analysis, and automation.

The first half of the curriculum focuses on research ideation and academic writing using generative AI. Participants will explore how AI models such as GPT can assist in the initial stages of research design by facilitating idea generation, topic refinement, and research planning. Through case-based demonstrations, attendees will learn to outline a research proposal, create a logical table of contents, and draft abstracts using AI assistance. Emphasis will be placed on the use of AI tools like Perplexity and Consensus for literature search, and Markdown for structuring academic documents. Practical sessions will guide participants through the process of creating a research topic and draft outline using AI prompts.

In the second half, attention shifts toward data analysis and automation using AI and Python. The session begins with foundational data handling techniques, where GPT is applied for spreadsheet-based tasks such as cleaning, normalization, and pattern analysis. The curriculum then delves into advanced statistical analysis, including regression and correlation, with an introduction to Python libraries like Pandas and Matplotlib for visualization and computation. Finally, the lecture covers Google Colab integration, demonstrating how researchers can automate data workflows—loading, preprocessing, modeling, and saving results—by combining Colab notebooks with GPT-generated code snippets.

Throughout the session, real-time demonstrations and hands-on activities will provide participants with the skills necessary to apply generative AI tools effectively in their own academic research. By the end of the lecture, attendees will gain not only technical know-how but also strategic insights into the ethical and practical use of AI in scholarly environments.

This session is ideal for early-career researchers, graduate students, and academic professionals seeking to leverage AI for enhanced productivity, creativity, and data-driven insight in their research processes.

Microorganisms are increasingly recognized not only as subjects of scientific investigation but also as catalysts for creative expression across disciplines. This presentation explores how microbiological knowledge and techniques are being integrated into artistic, educational, and design contexts, reframing microbes as active participants in cultural production. Recent developments in synthetic biology and microbial engineering have enabled novel applications such as agar art, which utilizes pigment-producing bacteria as living media, and bacterial sound research, which translates microbial activity into auditory forms through biosensing and sonification. These examples highlight the potential of microorganisms to serve as both material and metaphor in creative processes. By emphasizing the role of microbes in transdisciplinary innovation, this work proposes a new paradigm that bridges science and the arts. Such convergence not only broadens the scope of microbiological engagement but also encourages new ways of thinking about sustainability, collaboration, and the invisible networks that shape life and culture.