Women in Data Science: Changing the Paradigm

An occasion to spotlight women’s growing presence in analytics

Women in Data Science

With a consistently growing number of degrees awarded in data science each year, women in analytics are moving from having been underrepresented to growing in numbers and taking on leadership roles.

The goal of the conference was to inspire and educate — regardless of gender — and for women to share success stories while supporting each other.

Held at Penn’s Perry World House, the WiDS conference saw Wharton and Penn join more than 150 colleges and organizations hosting similar events focusing on inclusion and innovation. Through their work, the presenters and speakers at these events are challenging perceptions of the field.

  • The conference was co-sponsored by Analytics at Wharton, which unites the School’s six data-focused programs and was made possible by a transformative gift to the More Than Ever campaign.

The goal of the conference was to inspire and educate — regardless of gender — and for women to share success stories while supporting each other.

One story that inspired and educated the audience of 110 came from Melisa Lee, W’21, Zhun Yan Chang, W’21, and Emily Fu, W’21.

Fu, who is from California, explained she had been directly impacted by the state’s wildfire crisis. She and her teammates showed how it is possible to fight fire with random forest — a machine learning algorithm that consists of an ensemble of decision trees (and sits squarely in data science with no relation to the natural ecosystem).

  • By using random forest with data from the U.S. Forest Research Data Archive and the U.S. Department of Agriculture, the team determined the majority of large forest fires in California are caused by lightning strikes.
  • The team concluded the top vegetation fuel type predictor, timber litter, is highly correlated with lightning fires. They recommend cleaning up dry timber with controlled burns to remove the carpet of dead vegetation.
Women in Data Science Crowd

Other supporters of the conference included Wharton Customer Analytics, Wharton’s Statistics Department, and Penn Engineering.

“We learn analytics by doing analytics,” said Wharton’s Vice Dean of Analytics Eric T. Bradlow, addressing the attendees. “Women in data science is the most important initiative at the Wharton School in 25 years. You are in the right jobs, in the right places.”

Women in Data Science: Changing the Paradigm

An occasion to spotlight women’s growing presence in analytics

Women in Data Science

With a consistently growing number of degrees awarded in data science each year, women in analytics are moving from having been underrepresented to growing in numbers and taking on leadership roles.

The goal of the conference was to inspire and educate — regardless of gender — and for women to share success stories while supporting each other.

Held at Penn’s Perry World House, the WiDS conference saw Wharton and Penn join more than 150 colleges and organizations hosting similar events focusing on inclusion and innovation. Through their work, the presenters and speakers at these events are challenging perceptions of the field.

  • The conference was co-sponsored by Analytics at Wharton, which unites the School’s six data-focused programs and was made possible by a transformative gift to the More Than Ever campaign.

The goal of the conference was to inspire and educate — regardless of gender — and for women to share success stories while supporting each other.

One story that inspired and educated the audience of 110 came from Melisa Lee, W’21, Zhun Yan Chang, W’21, and Emily Fu, W’21.

Fu, who is from California, explained she had been directly impacted by the state’s wildfire crisis. She and her teammates showed how it is possible to fight fire with random forest — a machine learning algorithm that consists of an ensemble of decision trees (and sits squarely in data science with no relation to the natural ecosystem).

  • By using random forest with data from the U.S. Forest Research Data Archive and the U.S. Department of Agriculture, the team determined the majority of large forest fires in California are caused by lightning strikes.
  • The team concluded the top vegetation fuel type predictor, timber litter, is highly correlated with lightning fires. They recommend cleaning up dry timber with controlled burns to remove the carpet of dead vegetation.
Women in Data Science Crowd

Other supporters of the conference included Wharton Customer Analytics, Wharton’s Statistics Department, and Penn Engineering.

“We learn analytics by doing analytics,” said Wharton’s Vice Dean of Analytics Eric T. Bradlow, addressing the attendees. “Women in data science is the most important initiative at the Wharton School in 25 years. You are in the right jobs, in the right places.”

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