Head of Data Science
Talk title: The Human Side of Data Science
In my past five years at Airbnb, interest in data science as a discipline has quadrupled (according to Google Trends). It is exciting to be part of such a rapidly-evolving field. Alongside shifts in the larger industry, the Airbnb data science team has rapidly evolved to stay in step with Airbnb's hypergrowth, applying increasingly sophisticated techniques and methods to unlock scale. This talk will describe the evolution of data science work at Airbnb, including what is cutting edge in the three tracks of work we pursue: algorithms, analytics, and inference.
As the leader of Airbnb's Data team, Elena Grewald is responsible for driving the strategy for how Airbnb uses data for decision making and to infuse products and processes with algorithms. She started as one of the first data scientists at the company, where her initial work set up frameworks for understanding the impact of company initiatives - from the operations teams to the product teams. Her mission is to create a data-driven culture of experimentation at the company.
Prior to Airbnb, Elena received a Ph.D. in Education and an M.A. in Economics from Stanford University. Her dissertation used advanced statistical modeling to predict friendships in schools and analyzed how those friendships impacted the likelihood a lower income student enrolled in college. She received the Stanford Interdisciplinary Graduate Fellowship for this work. Originally from New Haven, Connecticut, she received a B.A. from Yale University studying Ethics, Politics, and Economics.
Chief Data Scientist
UN Global Pulse
Talk title: Data for Good: Towards a Rights-Based Approach to Research and Innovation
Making sure progress is equally distributed requires using new technologies that serve all people and ensure that we "leave no one behind." In September 2015, Member States of the United Nations adopted a set of goals to end poverty, protect the planet and ensure prosperity for all as part of a new global agenda. To achieve the SDGs, governments, private sector and civil society must work together. The UN is actively driving global discussions on how to harness the power of the data revolution to achieve this ambitious agenda. The work of the UN includes providing food and assistance to 80 million people, supplying vaccines to 45% of the world's children and assisting 65 million people fleeing war, famine and persecution. In this talk, UN Global Pulse will present applications of social data and other big data sources for sustainable development and humanitarian action. Examples of innovation projects will include: using social media to understand perceptions on refugees; using mobile data to map population movement in the aftermath of natural disasters; understanding recovery from shocks with financial transaction data; using satellite data to inform humanitarian operations in conflict zones or monitoring public radio to give voice to citizens in unconnected areas. Based on these examples, the session will discuss open challenges and opportunities for the research community to ensure that academic work can be translated into social impact. With the big data and the AI revolution, it is time to propose a shift to a rights-based approach to research and innovation.
Dr. Miguel Luengo-Oroz is the Chief Data Scientist at UN Global Pulse, an innovation initiative of the United Nations Secretary-General to safely and responsibly harness big data, AI, and other emerging technologies as a public good. As the first data scientist at the United Nations, since 2011, he has pioneered the use of big data for sustainable development and humanitarian action. Miguel has created and directed teams that have implemented over 30 innovation projects worldwide with governments and UN agencies. He is also the founder of MalariaSpot.org at the Universidad Politecnica de Madrid- a social innovation platform that leverages videogames, AI and 3D printing for medical diagnosis. Miguel is member or the expert group advising the government of Spain on Big Data and AI strategy. Prior to joining the UN, he worked as an antidisciplinary scientist in French and Spanish institutions in artificial creativity, medical imaging, genetics, bio-inspired image processing, neurogeometry, biometrics and developmental biology. Over the last 15 years he has co-authored more than 40 scientific publications and his work has been featured in international media including Le Monde, The Guardian, CNN or Al Jazeera. Miguel has been recognized as an Ashoka fellow, awarded the MIT Technology Review Social Innovator of the year and received the European Responsible Research and Innovation award. He holds a PhD and MSc in biomedical / telecommunications engineering from the Universidad Politecnica de Madrid and MSc in Cognitive Sciences from the Ecole des Hautes Etudes en Sciences Sociales de Paris.
School of Information, University of Michigan
Talk title: What's Missing When We Rely on Social Media Log Data (download slides here)
The first decade of ICWSM flourished under a growing abundance of social media user data (i.e., people's clicks and posts). As the community matures into its second decade, it is a good time to reflect on how that abundance has shaped our scholarship. This talk will examine what is missing when we focus on social media data generated by clicks and posts. Using experience sampling and eye-tracking methods, we are learning about people's internal states when they use social media, including how people feel when they post to social media, what they decide to share when posts are ephemeral, how they pay attention to other users' profiles, and what they pay attention to but do not click on. This talk will critically examine popular theories about social media use and will explore emerging research opportunities.
Sarita Schoenebeck is an Assistant Professor in the School of Information at the University of Michigan. She directs the Living Online Lab and is a co-founder of the Social Media Research Lab. Her research bridges human-computer interaction and social computing with a focus on studying and designing technology to address societal needs. Schoenebeck received her Ph.D in Human-Centered Computing from the Georgia Institute of Technology. She is a recipient of the NSF CAREER award and Best Paper and Honorable Mention awards at CHI. Her research has been covered in The New York Times, Washington Post, NPR, The Atlantic, NBC, ABC, CBS, and elsewhere.