Campus
- St. George
Fields of Study
- Philosophy of Science
- History of Science
Areas of Interest
history of neural networks; philosophy of statistics; philosophy of probability; formal epistemology.
Biography
Kye Palider is a PhD student at the IHPST, where he studies the history and philosophy of artificial neural networks. He has an MA in philosophy of science from the Department of Philosophy, University of Toronto, and an undergraduate degree in philosophy and mathematics from the University of Toronto, St. George.
Specifically, he studies how neural networks and their results came to be trusted, with emphasis on conceptions of error, analogies to biological neuron models, and relations of neural networks to statistics, probability, and formal epistemology. Furthermore, he is interested in how neural networks came to be used in the sciences at large, such as in computational biology, and how they came to be trusted despite their epistemic opacity.
In industry, Kye has worked in science publishing and in training AI in mathematical reasoning. He is working to complete the MITx Micromasters in Statistics and Data Science, a collection of graduate courses offered by the Massachusetts Institute of Technology in collaboration with edX, to further develop his technical and mathematical skills.