Courses

Machine Learning in Chromatography

Cover of a book titled 'Introduction to Artificial Intelligence in Chromatography' by Dr. Tijmen Bos & Dr. Bob Pirok, featuring a woman in a lab coat working with scientific equipment and a computer in a dark, wood-paneled room with classical sculptures and a clock.

  • Artificial intelligence (AI) is rapidly transforming science and society, from molecular discovery to advanced language models. Analytical separation science is no exception, with researchers seeking to harness AI’s potential to enhance data analysis, method optimization, and innovation. This course provides an introduction to AI within the context of chromatography and related analytical workflows, offering both foundational knowledge and applied insights.

  • The course begins with an accessible yet thorough introduction to AI, explaining its scope as a broad field encompassing numerous techniques, similar in diversity to chromatography itself. Participants will explore the most relevant AI methods for analytical chemistry, alongside their historical development and the technological “AI Winters” that slowed progress.
    A dedicated module addresses the limitations and challenges of AI, emphasizing the importance of understanding when and why certain techniques may fail, and recognizing situations where these limitations cannot be mitigated.
    The course then moves to a critical review of real-world AI applications in chromatography and data analysis, highlighting both successes and failures, and concludes with a forward-looking perspective on likely developments in the coming years.

    • Expert Guidance: In-depth explanations of core AI techniques, their potential, and their limitations in practical laboratory contexts.

    • Practical Exercises: Work with simulated chromatograms generated from randomized retention models or your own experimental data for personalized analysis.

    • Case Studies: Examples of successful and less successful AI applications in chromatography and analytical data processing.

    • Hands-On Session: Requires a Windows laptop capable of installing third-party software; performance may depend on computational power.

    • Interactive Demonstration Tool: A specialized software tool will be provided, enabling participants to simulate and assess the effects of AI on chromatographic optimization processes.