Mathematics, Synesthesia, and Personal Experiences

In this episode, Margot Gerritsen and Jon Krohn discuss the fundamentals of computational mathematics and its application in studying fluid dynamics. Margot also talks about how her synesthesia led to a lifelong interest in math, using computational mathematics to predict airflow, and why it is so important that underrepresented groups in data science become more visible through organizations like Women in Data Science.

This episode is brought to you by the Zerve data science dev environment, by Gurobi, the Decision Intelligence Leader, and by ODSC, the Open Data Science Conference. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• About computational mathematics and its relation to data science [03:19]
• Margot’s current research into emissions simulation [15:05]
• Computational Mathematics: Real-World Applications [33:18]
• The importance of wind tunnels in testing designs [47:54]
• The beauty of linear algebra [1:05:59]
• Synesthesia: Seeing Numbers as Colors [1:16:33]
• About Women in Data Science [1:24:59]

Additional materials: www.superdatascience.com/719