Math, Juggling, Hidden Markov Models, and Embedded Python

Explore the fascinating intersection of mathematics, juggling, and computer science in this 40-minute conference talk by Jan Dyre Bjerknes. Challenge common misconceptions about mathematics by using juggling as a unique starting point to uncover the deeper nature of mathematical concepts. Develop an abstract model of juggling, focusing on the power of abstraction in mathematics. Witness the practical application of this model through real-time analysis of juggling using Python-embedded balls. Embark on a historical journey connecting the abstract juggling model to ancient Greece, the Vatican, Japanese Origami, and even deep space exploration. Gain insights into Hidden Markov Models and their relevance to both juggling and broader mathematical concepts. Discover how seemingly disparate fields can be interconnected through the lens of mathematical abstraction and modeling.

Math, Juggling, Hidden Markov Models, and embedded Python - Jan Dyre Bjerknes