04-18, 16:40–17:15 (US/Eastern), Auditorium 3
An introduction to Geometric Algebra, with a focus on how it can (and can't) be used as a practical computational tool in Python. The discussion will present concrete examples which make use of the open source python library ‘Kingdon’. The audience should leave with a grasp of what GA is and what it isn't, so that they can decide if it is a tool worthy of their cognitive investment.
Geometric Algebra (GA) is a mathematical language that has recently received significant attention from the computer graphics and engineering communities. Proponents of GA claim that it provides a geometrically intuitive interface, concise syntax, and the ability to unify several of the most important algebras. This talk will discuss the pros and cons of GA as a practical computational tool in Python data science. The first half of the talk will introduce the concepts of GA, and the second half will provide concrete demonstrations with the Kingdon library.
While geared toward data scientists, this talk can be enjoyed by anyone interested in applied mathematics. A basic background in linear algebra will be helpful. Additionally, those using vector algebra, complex numbers, quaternions, rotation matrices and the like will be especially interested. The audience should leave with a grasp of what GA is and what it isn't, so that they can decide if it is a tool worthy of their cognitive investment.
Previous knowledge expected
Alex has worked as a data scientist, library builder, and math enthusiast with over 12 years of experience. He holds a B.S. and Ph.D. in Electrical Engineering from the University of Virginia (2007, 2012), where he specialized in microwave systems and applied mathematics. He founded Eight Ten Labs (810lab.com) in 2016, and has developed and maintained two widely adopted open-source Python libraries, scikit-rf and clifford, has authored over 25 scientific papers, and holds a U.S. patent (No. 10459018) in electronic measurement systems.