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Tune in, and get inspired with WiDS

Get to know the women behind the data science. Leading women in data science share their work, advice, and lessons learned. Hear about how data science is being applied and having impact across a wide range of domains. Join hosts Margot Gerritsen and Chisoo Lyons in the open and informal conversations with our many inspiring guests.

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  • Cover Photo for The Power of Linguistics in Large Language Models and AI

    Episode 51

    Karin Golde | The Power of Linguistics in Large Language Models and AI

    Listen to Karin Golde, a linguistic expert and AI entrepreneur, as she discusses the rise of large language models (LLMs) and the impact of ChatGPT. Karin reflects on the unexpected popularity of LLMs and the role of OpenAI. The challenges and limitations of LLMs are discussed, including the need for human understanding emphasizing the need for diverse perspectives and cultural understanding in AI development. Karin shares her personal experience of using LLMs and highlights the importance of balancing innovation with regulation in the AI industry. Karin concludes the podcast sharing about her career journey and her recent transition to working as an independent consultant. She offers advice for women considering leadership roles and emphasizes the importance of thinking broadly about one’s place in an organization.

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  • Cover Photo for Researching Algorithmic Fairness and Causal Inference in Public Health

    Episode 33

    Allison Koenecke | Researching Algorithmic Fairness and Causal Inference in Public Health

    Allison Koenecke, currently a postdoc at Microsoft Research and soon to be assistant professor at Cornell, discusses her decision to pursue a career in academia focused on algorithmic fairness and causal inference in public health.

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  • Cover Photo for Building Bridges Between Business and Academia

    Episode 32

    Karina Edmonds | Building Bridges Between Business and Academia

    Karina Edmonds, Global Head of Academies and University Alliances at SAP, has spent her career building bridges between business and academia. She is passionate about promoting fairness in data science by bringing more young people, women, and underrepresented groups into the field.

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  • Cover Photo for Applying Machine Learning to Understand and Improve Health

    Episode 13

    Marzyeh Ghassemi | Applying Machine Learning to Understand and Improve Health

    Marzyeh Ghassemi, an assistant professor at the University of Toronto, is focused on Healthy ML—applying machine learning to understand and improve health.

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EP. 24
English
Femke Vossepoel |

Applying Data Assimilation Tools to COVID Forecasting Models

TOPICS: Algorithms, Data Generation/Collection, Data Wrangling

Femke Vossepoel, Professor in Geoscience and Engineering at Delft University of Technology in the Netherlands, explains how data assimilation tools can be used to improve COVID-19 forecasting models.

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EP. 23
English
Rachel Nethery Francesca Dominici |

Using Data Science to Study Air Pollution Effect on COVID-19 Outcomes

TOPICS: Data Generation/Collection, Data Science as a Career

Francesca Dominici and Rachel Nethery, from Harvard University’s T.H. Chan School of Public Health, are working to inform public health policy through research at the intersection of environmental health science, data science, climate change and health policy.

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EP. 22
English
Manisha Desai |

The Importance of Data Integrity in COVID-19 Clinical Trials

TOPICS: Data Generation/Collection, Data Wrangling

Manisha Desai, professor of medicine and biomedical data science at Stanford University, shares some insights about the challenges and progress of current COVID-19 clinical trials.

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EP. 21
English
Newsha Ajami, PhD |

Improving Urban Water Systems Through Data Science, Public Policy and Engineering

TOPICS: Algorithms, Data Generation/Collection

Newsha Ajami, director of Urban Water Policy with Stanford University’s Water in the West, focuses on improving urban water systems through interdisciplinary research combining data science, engineering and public policy.

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EP. 20
English
Andrea Gagliano |

The Intersection of Arts and Technology

TOPICS: Algorithms, Data Generation/Collection

Andrea Gagliano, Head of Data Science, AI and Machine Learning at Getty Images, works at the intersection of art and technology — using machine learning to inspire creativity, and the arts to comprehend technology.

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EP. 19
English
Ya Xu |

Using Data To Create Economic Opportunities For All Members Of Global Workforce

TOPICS: Data Generation/Collection, Values

Ya Xu, head of LinkedIn’s global data science team, explains how the company takes responsibility for data privacy and creating economic opportunities for all of its members.

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EP. 18
English
Susan Athey |

Bringing an Economist’s Perspective to Data Science

TOPICS: Algorithms, Data Science as a Career, Values

Susan Athey, Economics of Technology Professor at the Stanford Graduate School of Business, brings an economist’s expertise and perspective to machine learning and data science.

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EP. 17
English
Montse Medina |

Lessons Learned Building a Data Science Startup

TOPICS: Data Science as a Career

Montse Medina, a successful data science entrepreneur, is currently a partner at Deloitte in Spain responsible for the firm’s advanced analytics and asset-enabled business.

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EP. 16
English
Timnit Gebru |

Advocating for Diversity, Inclusion and Ethics in AI

TOPICS: Values

Timnit Gebru spoke to us when she was a research scientist and technical co-lead of Google’s Ethical Artificial Intelligence Team. In this episode, Timnit explains the importance of advocating for diversity, inclusion and ethics in AI.

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Podcast Hosts

Professor Margot Gerritsen

Margot Gerritsen was born and raised in the Netherlands, and after getting her PhD at Stanford, she.spent time in New Zealand in the Department of Engineering Science at the University of Auckland, returning to Stanford in 2001 as faculty member in Energy Resources Engineering. Margot specializes in the development of computational methods for renewable and fossil energy production. She is also active in coastal ocean dynamics and yacht design, as well as several other areas in computational mathematics including search algorithm design and matrix computations. Margot also Chairs the Board of Trustees for SIAM (Society for Industrial and Applied Mathematics).

Chisoo Lyons

Chisoo was born in South Korea and grew up living in Indonesia, Germany, and Jordan, before moving to the US. She attended University of California Berkeley and received a bachelor’s degree in Industrial Engineering & Operations Research and continued with her master’s focusing on Operations Research. Living in different parts of the world cultivated her ever-present curiosity about people and cultures. Chisoo worked for FICO, a global analytic and decision management company, applying data science to developing, consulting, and implementing decision support solutions for her clients. Her corporate career culminated in leadership roles managing innovation and lines of business. Now, as the Chief Program Director of Women in Data Science, Chisoo is thrilled to be in service of a global community of amazing women doing extraordinary work in the field of data science.

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