BIDS Spring 2017 Data Science Faire


May 2, 2017
1:30pm to 4:30pm
190 Doe Library
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Join us May 2 for our Spring 2017 Data Science Faire to close out BIDS' third academic year and celebrate data science at Berkeley.

We hear the word "data" almost every day on campus and in the news. But, did you ever wonder what UC Berkeley students, faculty, and researchers are doing with data and what interesting findings they have uncovered? At this year's Data Science Faire, we will showcase exciting data-intensive initiatives at BIDS and UC Berkeley, highlighting work from the diverse community of data scientists around campus. Learn more about the exciting open source projects BIDS affiliates are working on and catch up on the work of researchers at some of Berkeley’s top data science centers.



This year’s Data Science Faire will feature a wide variety of poster/demo exhibits from students and researchers on campus as well as a series of data science–related lightning talks from BIDS fellows. The event will culminate with keynote address from Lorena Barba, Associate Professor of Engineering and Applied Science, George Washington University.

1:30 p.m. Event Opens
1:50 p.m. Welcome/Intro - Saul Perlmutter and Kevin Koy
BIDS Director and Executive Director
2:10 p.m. Lightning Talk (5 min.) - Rebecca Barter
PhD Student, Department of Statistics; BIDS Data Science Fellow
Superheat: An r package for generating beautiful, extendable, customizable heatmaps
2:30 p.m. Lightning Talk (5 min.) - Chris Holdgraf
Graduate Researcher, Helen Wills Neuroscience Institute; BIDS Data Science Fellow
Studying sound in the human brain using predictive models
2:50 p.m. Lightning Talk (5 min.) - Nelle Varoquaux
Postdoctoral Scholar, Department of Statistics; BIDS Data Science Fellow
Better understanding gene regulation through the integrative analysis of heterogeneous Datasets
3:10 p.m. Lightning Talk (5 min.) - Stuart Geiger
BIDS Ethnographer
Academic careers in data science: results from the msdse career survey
3:30 p.m. Lightning Talk (5 min.) - Nick Adams
 BIDS Research Fellow–Social Sciences
Qualitative text analysis at a quantitative scale
3:50 p.m. Lightning Talk (5 min.) - Orianna DeMasi
Graduate Student Researcher, Department of Electrical Engineering and Computer Science; BIDS Data Science Fellow
sensing wellbeing to improve mental health care
4:10 p.m. Keynote (20 min.) - Lorena Barba
Associate Professor, Mechanical and Aerospace Engineering, The George Washington University
Data science for all
Data Science—understood broadly as a merger between computation, statistics, data management, and real-world applications—permeates through every sector of modern society. Innovative companies are developing data products galore, creating wealth and changing our daily habits: how we shop, how we commute, how we learn. Beyond products, algorithms are used to feed us advertisement and “news,” marshal police patrols in line to crime predictions, and even select the “right” employee for a position. Automatic systems are judging us. And not only do they reflect the inequalities of society, they can inflame our differences. In this new world, every citizen needs data science literacy. UC Berkeley is leading the way on broad curricular immersion with data science, and other universities will soon follow suit. The definitive data science curriculum has not been written, but the guiding principles are computational thinking, statistical inference, and making decisions based on data. “Bootcamp” courses don't take this approach, focusing mostly on technical skills (programming, visualization, using packages). At many computer science departments, on the other hand, machine-learning courses with multiple pre-requisites are only accessible to majors. The key of Berkeley’s model is that it truly aims to be “Data Science for All.”

Our industry partners, Siemens and State Street, will also be available at the faire to showcase their efforts in data science and discuss career opportunities at their organizations.



Live 3D Demo!

We hear much about virtual reality and reality capture, but what do these terms really mean and what kinds of reality are being captured? Benjamin von Cramon shares his experiences that led him to develop a 3D capture system, novel in its ability to model complex interior spaces, to change the lighting in imagery after pictures are taken. As an example of such photorealistic virtual environments, Benjamin will host live 3D HD tours of a remote cave in Texas Hill Country.



Lorena Barba

Associate Professor of Engineering and Applied Science, George Washington University

Lorena Barba is an associate professor of engineering and applied science at the George Washington University in Washington, DC. Previously, she held faculty positions in mechanical engineering at Boston University and in applied mathematics at the University of Bristol, UK. She has a PhD in aeronautics from the California Institute of Technology (2004). Her research interests include computational fluid dynamics, especially immersed boundary methods and particle methods for fluid simulation; fundamental and applied aspects of fluid dynamics, especially flows dominated by vorticity dynamics; aerodynamic aspects of animal flight; boundary element methods and their application to electrostatics of biomolecules; the fast multipole method and applications; and scientific computing on GPU architecture. Professor Barba is an Amelia Earhart Fellow of the Zonta Foundation (1999), a recipient of the EPSRC First Grant program (UK, 2007), an NVIDIA Academic Partner award recipient (2011), and a recipient of the NSF Faculty Early CAREER award (2012). She was named CUDA Fellow by NVIDIA, Corp., and is a leader in computational science and engineering internationally.