The 5th Annual Women in Data Science (WiDS) Datathon will launch in January, in advance of the WiDS Worldwide Conference to be held on March 7th, 2022. This year’s WiDS Datathon, organized by the WiDS Worldwide team, Stanford University, Harvard University IACS, and the WiDS Datathon Committee, will address an important way to mitigate the effects of climate change with a focus on energy efficiency. The WiDS Datathon Committee is partnering with experts from many disciplines at Climate Change AI, Lawrence Berkeley National Laboratory (Berkeley Lab), US Environmental Protection Agency (EPA), and MIT Critical Data.

Data science is a crucial tool to quantify, predict and communicate about the impact of climate change. For example, a recent study used machine learning to analyze over 100,000 weather events that could be linked to global warming and discovered that 80 percent of the earth’s land has been adversely impacted and at least 85 percent of the world’s population has been affected by extreme weather events caused by climate change.

The Women in Data Science (WiDS) Conference and podcast series has been showcasing leading women data science experts who are using data science to help us understand the impact and potential solutions to combat climate change. Our WiDS Datathon 2022 dataset will also be focused on the impacts of climate change.
 
Here are some recent podcasts, panels, and talks from our WiDS conferences that address sustainability.

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, on a recent WiDS Podcast episode.

Register now for the Women in Data Science (WiDS) Worldwide conference 2022, a technical conference featuring outstanding women discussing their exceptional work in data science and related fields, in a wide variety of research domains. All genders are welcome and encouraged to attend!​

Data scientists work with large data sets that require computational analysis to gain insights and knowledge that often drive important decisions within organizations in industry, academia, non-profits, and government. In order for these insights to have the desired impact, data scientists need to communicate clearly to be well--and quickly--understood. Data visualization allows data scientists the ability to provide unique views into the data and about the data, turning data sets into insights at-a-glance. ​

Suzanne Valentine, Facebook’s Director of Data Science for Global Marketing Solutions, has built her career turning data into business insights. Inspired by WiDS’ support for women data scientists, Facebook has become a sponsor, providing micro-scholarships for WiDS ambassadors.

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

We live in an era of big data with data sets that require computational analysis to gain insights and knowledge. The volume of big data has been increasing steadily, and will only continue to climb. Since we started the WiDS initiative in 2015, Statistica estimates that the volume of data has increased from 15.5 to 74 zetabytes, and they forecast that data volume will double again by 2024.

Yet with all of this data, one of the biggest challenges that data scientists and researchers face is dealing with missing data. In some cases, the missing data is due to not readily having access to the data sets that are required to perform the analysis, while other cases involve data sets that are incomplete and not uniformly populated.

​Sulakshana Sreeram, Assistant Director of Corporate Relations & Initiatives at Sri Vishnu Education Society, is the WiDS Hyderabad Ambassador and a collaborator with the WiDS Education Outreach program.

​Fatima Abu Salem, a professor at the American University of Beirut, talks about how the conflict in the region has shaped her life journey and motivates her to apply data science for the public good to address challenges in Lebanon, on a recent WiDS Podcast episode.

Data science is being applied in a growing number of domains that affect everyone’s lives, in healthcare, financial services, agriculture, resource management, and beyond.  While data science has huge potential for good, there are also unintended consequences. Data scientists need to take steps  to mitigate as many unintended consequences as they can using Responsible Data Science — a set of policies, procedures, and best practices to ensure algorithmic fairness, transparency, and explainability. 

The Women in Data Science (WiDS) Conference and podcast series has been showcasing  leading women data science experts who are making an impact at the forefront of COVID research. Here are three talks from the conference and three podcasts: