Researching algorithmic fairness and causal inference in public health with Allison Koenecke11/11/2021
Gaining skills and overcoming barriers to a career in data science with Louvere Walker-Hannon8/12/2021
 With the onset of the COVID-19 pandemic, Francesca Dominici and Rachel Nethery of Harvard T.H. Chan School of Public Health saw a way to connect the research they were doing on air pollution and health with the pandemic. On a recent episode of the WiDS Podcast, they discuss how they are studying the effects of air pollution exposure on different causes of hospitalization to see if pollution could increase a person's vulnerability to COVID-19. While the research is at a preliminary stage, there is a lot of information that points towards the possibility that long-term exposure to air pollution could increase the mortality risk for COVID-19.
 Manisha Desai is a professor of medicine (research) and of biomedical data science, and director of the Quantitative Sciences Unit at Stanford University. She is an expert in the design and analysis of clinical trials and epidemiologic studies across multiple diseases, including COVID-19. In a recent episode of the WiDS Podcast, she provides some insights into the challenges and progress of COVID-19 clinical trials.
Improving Urban Water Systems Through Data Science, Public Policy and Engineering with Newsha Ajami6/3/2020
 Newsha Ajami is a hydrologist specializing in sustainable water resource management, water policy, the water-energy-food nexus, and urban water strategy. When she was studying hydrology in grad school, she took a water policy class that changed the trajectory of her career. "I would say that was one of the most important events in my professional career. I realized that laws and policies are what change the way we manage resources,” she says. All the data optimization and modeling means nothing unless you can understand the policy layer imposed on how our natural systems operate.
 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. She speaks with Professor Margot Gerritsen on the WiDS Podcast.
Using Data To Create Economic Opportunities For All Members Of Global Workforce with Ya Xu4/15/2020
 Ya Xu manages LinkedIn’s global team of data scientists that manage data science projects across the company’s products, sales, marketing, economics, infrastructure, and operations. On a recent episode of the WiDS Podcast, she says the company takes active responsibility over the data they collect to ensure fairness and protect privacy. They are very proactive about how they maintain their members’ trust, either with how they share the data externally or leverage the data to create opportunities.
 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, during an in-depth conversation with Professor Margot Gerritsen on the Women in Data Science (WiDS) Podcast.
 Montse Medina was pursuing her PhD at Stanford’s Institute for Computational and Mathematical Engineering (ICME) when she realized she had a great idea for a company. She left her graduate program to found Jetlore, a prediction platform that empowers retailers with AI-driven content, which was acquired by PayPal in 2018. Montse has since moved back to her native Spain as a partner for Deloitte where she is responsible for their advanced analytics and asset-enabled business. Montse discusses her lessons learned growing Jetlore with Margot Gerritsen, Stanford professor and host of the Women in Data Science (WiDS) Podcast.
 It was in 2015 when Margot Gerritsen was asked to speak at a data conference with not a single other woman on the program that she knew that something had to be done to get women into the field. She tells the story of how WiDS got started, with Professor Russ Altman and host of Stanford Engineering’s Future of Everything podcast.
 Timnit Gebru, a research scientist and technical co-lead of Google’s Ethical Artificial Intelligence Team, explains the importance of advocating for diversity, inclusion and ethics in AI on the Women in Data Science (WiDS) Podcast.
 Sherrie Wang, a fourth year PhD student at Stanford’s Institute for Computational and Mathematical Engineering (ICME), explains on the Women in Data Science (WiDS) Podcast how she applies machine learning methods to help solve global food security challenges.
 Marzyeh Ghassemi, an assistant professor at the University of Toronto, is focused on Healthy ML — applying machine learning to understand and improve health.
|
RSS Feed