Keynote Speakers

Casey Fiesler

Casey Fiesler

Title: Data Is People: Ethics and Education for Data Science

Abstract: Big data has opened up new possibilities and transformed the ways we conduct research in nearly every discipline. However, ethical considerations and education for research has long focused on human subjects, governed in the U.S. by institutional review boards. Data science often falls through the cracks of these regulations, so it is even more imperative that we have strong ethical norms and guidelines. This starts with the reminder that though data scientists may not interact directly with people, the data collected and analyzed very often comes from people, which opens up important considerations around privacy, consent, and harm. Moreover, applications of data science research, particularly with respect to prediction, have the potential for large-scale societal impacts. In considering the broad landscape of technology ethics when it comes to uses and applications of big data, I will argue for a fundamental shift in how we teach ethics to future data scientists and researchers.

Bio: Dr. Casey Fiesler researches and teaches in the areas of technology ethics, internet law and policy, and online communities.

She is a Fellow in the Silicon Flatirons Institute for Law, Technology, and Entrepreneurship, an ATLAS Fellow, and holds a courtesy appointment in Computer Science.

Also a public scholar, she is a frequent commentator and speaker on topics of technology ethics and policy, as well as women in STEM (including consulting with Mattel on their computing-related Barbies). Her work on research ethics for data science, ethics education in computing, and broadening participation in computing is supported by the National Science Foundation, as well as Mozilla and Omidyar Network as part of the Responsible Computer Science Challenge.



Stefan van der Walt

Stéfan van der Walt

Title: Unboxing Data Science: Opportunities and Challenges of Open Work

Abstract: Data science is a new discipline.  As such, we have a greater opportunity than in many other fields to define what its culture should look like.  In this talk, I discuss how open approaches to software, research, and education improve science, but also challenge the way in which we approach our work. 

Bio: Dr. Stéfan van der Walt is a senior research data scientist at the Berkeley Institute for Data Science, the founder of scikit-image, and co-author of "Elegant SciPy: The Art of Scientific Python".

Stéfan has been developing scientific open-source software for more than fifteen years, focusing primarily on tools in the Python language. He is a director of NumFOCUS, and serves on the steering committees of NumPy, SciPy, and the Python Software Foundation's Scientific Working Group.  Outside (and sometimes during) work, he is kept on his toes by two energetic toddlers, and he enjoys running in the great outdoors.




Fall 2020 Data Science Symposium

Symposium Schedule
Start       codeEndEvent
9:00 am9:15 amOpening Remarks
9:15 am             63 48 79 910:15 amKeynote Speaker: Fiesler
10:15 am10:45 amCoffee Break
10:45 am           41 87 47 612:15 pmEducation Session Talks
12:15 pm1:00 pmLunch Break
1:00 pm             74 73 30 52:00 pmKeynote Speaker: van der Walt
2:00 pm             35 92 12 13:00 pmResearch Session Presentations and Discussion
3:00 pm3:30 pmCoffee Break or continued discussion
3:30 pm             96 06 04 04:30 pmIndustry Session Talks
4:30 pm5:00 pmA Discussion on Data Science at CU Denver and Closing Remarks