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Contribution to Gammerman Festschrift

I am honored to announce a new book chapter in "The Importance of Being Learnable", a volume of essays dedicated to Alexander Gammerman on the occasion of his 80th birthday.

Prof. Gammerman is a foundational figure in AI uncertainty quantification and the co-inventor of the Conformal Prediction algorithm.

Together with Lars Carlsson, Ernst Ahlberg, and James Gammerman, I co-authored the chapter "Application of Confidence and Probabilistic Models to Practical Problems".

Our contribution surveys the transformative impact of the methods Gammerman pioneered, examining their adaptation to real-world challenges in:

  • Drug Discovery: High-stakes decision-making with valid uncertainty.

  • Autonomous Systems: Enhancing safety in self-driving technologies.

  • NLP: Mitigating hallucinations in Large Language Models.

  • Industrial Engineering: Optimizing maintenance schedules and anomaly detection.

The volume recognizes Gammerman's long-lasting impact as a researcher, educator, and mentor, celebrating a career that spans from pioneering mathematical models of plant photoreceptors to advancing the formal treatment of uncertainty in AI.