This week for The Hacker Within, Stuart Geiger will be teaching us about Jupyter Notebooks. Full details can be found on the THW website. All are welcome, and please forward this invitation to those who might be interested.
The Hacker Within is a weekly peer learning group for sharing skills and best practices for scientific computation and data science.
I’m an ethnographer of science and technology, and I study the infrastructures and institutions that support the production of knowledge. Most of my previous work has been on Wikipedia, where I’ve studied the community of volunteer editors who produce and maintain an open encyclopedia. I’ve also studied distributed scientific research networks and projects, including the Long-Term Ecological Research Network and the Open Science Grid. In Wikipedia and scientific research, I’ve studied topics including newcomer socialization, community governance, specialization and professionalization, quality control and verification, cooperation and conflict, the roles of support staff and technicians, and diversity and inclusion. And, as these communities are made possible through software systems, I’m very interested in how the design of software tools and systems intersect with all of these issues.
I’m an interdisciplinary nomad who loves collaborating with people who use other kinds of methods and approaches. I began college as a computer science major at UT-Austin but switched to philosophy halfway through and got a degree in humanities. I got my MA in the Communication, Culture, and Technology program at Georgetown University, where I began empirically studying communities using qualitative and ethnographic methods. Then, I went to the UC-Berkeley School of Information for my Ph.D and worked with anthropologists, sociologists, psychologists, historians, organizational and management scholars, designers, and computer scientists. In terms of academic fields, I spend much of my time in science and technology studies, computer-supported cooperative work, and new media studies. I’m very excited to be bringing these approaches and methods to the challenges and opportunities of data science.