Bridget Kennedy - I'll give a number of examples of problems that arise in my work in computer vision and general machine learning, and discuss how creative problem solving, linear algebra, and statistics are superpowers mathematicians in industry use to solve real world problems.  

Ashley Anhalt - I will focus on several mathematical techniques I have applied to my jobs in industry (including machine learning, anomaly detection, statistical analysis, and data visualization), as well as speak to the need for recognizing and embracing different communication techniques for varying audiences (from model review boards to non-technical business partners).

 

Daniel Champion - I will discuss the role of a mathematical scientist in diagnostic and experimental physics through a multidisciplinary shock physics and measurement innovation example.

Ivan Barrientos - I will provide a brief overview of the "day to day" of applied ML and deep learning in large tech companies.

Toby Shearman - I will give a quick intro to the autonomous vehicle space and try to hit some of the interesting probabilistic and mathematical ideas that we regularly use. 

Kyle Pounder - I will give a quick tour, using examples, of the experimentation and causal inference problems that come up in my work in product analytics.