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Вміст надано Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.
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Karina Edmonds | Building bridges between business and academia

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Manage episode 304185544 series 2706384
Вміст надано Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.

Though Karina showed an early aptitude in math, her high school counselor advised her against pursuing an engineering degree. She ignored his advice and went on to earn her undergrad degree in mechanical engineering from the University of Rhode Island and a PhD in Aeronautics from Caltech. She landed her first job as a speech-to-text engineer at TRW where she was awarded her first patent. She then moved on to technology transfer as a patent agent at the Jet Propulsion Lab. She bounced back to academia, managing corporate partnerships for Caltech, and then returned to industry as Google’s University Lead for Google Cloud AI/Machine Learning. She is now at SAP as Global Head of Academies and University Alliances, continuing to connect industry and academia.

In her diverse career spanning business and education, she has seen increasing power concentrated in big tech companies through their ownership of immense datasets and computational power. Companies are also attracting talent away from universities that are now having a hard time hiring enough computer science faculty. She says there are some creative ways to bring back some balance by companies hosting visiting faculty and industry partners coming in to teach at universities.

Karina is also very concerned about ensuring fairness in data science. She explains that it’s not just the software that's being developed, but the datasets that are used to create predictive models. If a company just collects data from one demographic and then applies it to everyone, that introduces bias, and then the algorithms amplify these biases. She believes that the only way to address this is to have more ethnic, gender and geographic diversity in the field of data science. She sees a vital need to encourage more women and minorities to enter the field to bring diverse perspectives to data science.

For people interested in pursuing a career in data science, she advises gaining the basic skills in math, science, and programming languages, but the most important quality is the ability to learn because everything is constantly changing. She recommends keeping your options open, acquiring as many skills as possible, and sharpening your interpersonal skills. Karina also says to challenge yourself. “We don't grow in a space of comfort. You grow when you're challenged, it's okay to be uncomfortable because that's likely the place of greatest growth. There’s no such thing as failure, you either win or you learn.”

RELATED LINKS
Connect with Karina on LinkedIn and Twitter
Find out more about SAP
Connect with Margot Gerritsen on Twitter (@margootjeg) and LinkedIn
Find out more about Margot on her Stanford Profile

  continue reading

51 епізодів

Artwork
iconПоширити
 
Manage episode 304185544 series 2706384
Вміст надано Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Stanford Women in Data Science (WiDS) initiative, Professor Margot Gerritsen, and Chisoo Lyons або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.

Though Karina showed an early aptitude in math, her high school counselor advised her against pursuing an engineering degree. She ignored his advice and went on to earn her undergrad degree in mechanical engineering from the University of Rhode Island and a PhD in Aeronautics from Caltech. She landed her first job as a speech-to-text engineer at TRW where she was awarded her first patent. She then moved on to technology transfer as a patent agent at the Jet Propulsion Lab. She bounced back to academia, managing corporate partnerships for Caltech, and then returned to industry as Google’s University Lead for Google Cloud AI/Machine Learning. She is now at SAP as Global Head of Academies and University Alliances, continuing to connect industry and academia.

In her diverse career spanning business and education, she has seen increasing power concentrated in big tech companies through their ownership of immense datasets and computational power. Companies are also attracting talent away from universities that are now having a hard time hiring enough computer science faculty. She says there are some creative ways to bring back some balance by companies hosting visiting faculty and industry partners coming in to teach at universities.

Karina is also very concerned about ensuring fairness in data science. She explains that it’s not just the software that's being developed, but the datasets that are used to create predictive models. If a company just collects data from one demographic and then applies it to everyone, that introduces bias, and then the algorithms amplify these biases. She believes that the only way to address this is to have more ethnic, gender and geographic diversity in the field of data science. She sees a vital need to encourage more women and minorities to enter the field to bring diverse perspectives to data science.

For people interested in pursuing a career in data science, she advises gaining the basic skills in math, science, and programming languages, but the most important quality is the ability to learn because everything is constantly changing. She recommends keeping your options open, acquiring as many skills as possible, and sharpening your interpersonal skills. Karina also says to challenge yourself. “We don't grow in a space of comfort. You grow when you're challenged, it's okay to be uncomfortable because that's likely the place of greatest growth. There’s no such thing as failure, you either win or you learn.”

RELATED LINKS
Connect with Karina on LinkedIn and Twitter
Find out more about SAP
Connect with Margot Gerritsen on Twitter (@margootjeg) and LinkedIn
Find out more about Margot on her Stanford Profile

  continue reading

51 епізодів

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