Tommaso Flaminio is a Ramón y Cajal Researcher at the Artificial Intelligence Research Institute (IIIA), of the Spanish National Research Council. His research focusses on problems arising from uncertain reasoning, artificial intelligence and decision theory. With an academic background in mathematical logic and theoretical computer science, he develops new methods and techniques ranging from algebra to convex geometry, category theory, functional analysis and measure theory.
The project much profited by discussing foundational issues of reliable inference, techniques of reliable inference and foundations of rational inference with Tommaso Flaminio.
Bennett Holman an Assistant Professor of History and Philosophy of Science at Underwood International College at Yonsei University (Seoul, South Korea). He is interested in developing the intersection between medical and social epistemology. His current project is focused on articulating how scientific epistemology must be altered in areas of science that are heavily influenced by industry funding. Specifically, in areas such as medical (especially pharmaceutical) research: How should we evaluate and interpret evidence given that it is not produced as a good-faith effort by a community of truth-seekers? How can including the social dimension into epistemology bring to light problems that are obscured by focusing on an isolated knower confronting a fixed set of data? Finally, what are the ethical implications of the new role that scientific evidence is playing in medical decision making?
Professor Holman’s visit to the MCMP and continued exchange has helped and continues to help the project team in a number of ways. Of particular value are his insights into the social realm of medical epistemology.
Glenn Shafer is Professor at the Rutgers Business School – Newark and New Brunswick. He obtained his Ph.D. in mathematical statistics in 1973 from Princeton University. During is academic life he made numerous contributions to mathematics, statistics, and finance. He is one of the founding fathers of the Dempster-Shafer-Theory, which is a mathematical framework for modelling epistemic uncertainty. Among his most recent books “Probability and Finance: It’s Only a Game!” (2001, co-authored by Vladimir Vovk) provides a foundation for probability based on game theory rather than measure theory. “Algorithmic Learning in a Random World” (2005), a joint work with Vladimir Vovk and Alex Gammerman, describes how several important machine learning problems, such as density estimation in high-dimensional spaces, cannot be solved if the only assumption is randomness. Glenn Shafer has research interests in a great number of fields which led to publications in journals in statistics, philosophy, history, psychology, computer science, economics, engineering, accounting, and law. For more information, visit his website.
Professor Shafer’s expertise and views on evidence, evidence supporting hypotheses and uncertainty greatly stimulated the project team’s approach.
Here, you can read more about the seminar he thought at the MCMP.