Applying topological data analysis and geometry-based ML
Media Type |
audio
Categories Via RSS |
Education
Science
Technology
Publication Date |
Feb 22, 2024
Episode Duration |
00:28:24

 

Highlights:

 

  • 00:02:25 - Colleen’s motivation for writing a book, interdisciplinary collaborations, and explaining advanced mathematical tools in accessible ways.
  • 00:08:44 - Journey from biology and social sciences to data science, and the integration of different mathematical tools in solving data problems.
  • 00:14:13 - Overcoming imposter syndrome and the value of exploring beyond one's field.
  • 00:15:02 - The importance of mentorship.
  • 00:23:40 - Coping strategies for setbacks in academia and industry.

About the Guest:

Colleen Farrelly is an author and senior data scientist. Her research has focused on network science, topological data analysis, and geometry-based machine learning. She has a master's from the University of Miami and has experience in many fields, including healthcare, biotechnology, nuclear engineering, marketing, and education. Colleen wrote the book, The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R

 

Mentions:

Connect with Colleen Farrelly on LinkedIn

 

Related Links:

The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R

 

Connect with Us

Margot Gerritsen on LinkedIn

Listen and Subscribe to the WiDS Podcast on Apple Podcasts,Google Podcasts,Spotify,Stitcher

Margot Gerittsen speaks with Colleen Farrelly, Mathematician at Post Urban Ventures and Author of The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R. Colleen is known for network science, topological data analysis, and geometry-based machine learning. This podcast covers the challenges and rewards of interdisciplinary work and her journey in the discipline of data science.

 

Highlights:

 

  • 00:02:25 - Colleen’s motivation for writing a book, interdisciplinary collaborations, and explaining advanced mathematical tools in accessible ways.
  • 00:08:44 - Journey from biology and social sciences to data science, and the integration of different mathematical tools in solving data problems.
  • 00:14:13 - Overcoming imposter syndrome and the value of exploring beyond one's field.
  • 00:15:02 - The importance of mentorship.
  • 00:23:40 - Coping strategies for setbacks in academia and industry.

About the Guest:

Colleen Farrelly is an author and senior data scientist. Her research has focused on network science, topological data analysis, and geometry-based machine learning. She has a master's from the University of Miami and has experience in many fields, including healthcare, biotechnology, nuclear engineering, marketing, and education. Colleen wrote the book, The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R

 

Mentions:

Connect with Colleen Farrelly on LinkedIn

 

Related Links:

The Shape of Data: Geometry-Based Machine Learning and Data Analysis in R

 

Connect with Us

Margot Gerritsen on LinkedIn

Listen and Subscribe to the WiDS Podcast on Apple Podcasts,Google Podcasts,Spotify,Stitcher

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