Write a Blog >>
Sun 22 - Fri 27 October 2017 Vancouver, Canada
Thu 26 Oct 2017 15:30 - 16:00 at Regency D - Machine Learning & Data Science Chair(s): Cristina Cifuentes

Data-driven sciences are poised to transform our society by fostering innovation, enabling better decision making, and driving organizational and sector changes. Availability of data with adequate permission, the so called “open data,” is the secret sauce enabling this transformation. But, access to data alone is insufficient because of significant barriers that exist in obtaining and using big data. Datadriven scientists are effectively facing a new digital divide between those who have data, bandwidth, deep expertise, well-established data-mining infrastructures, and those who don’t. There are efforts to simplify large-scale data analysis; however, we do not yet have user centric solutions that democratize innovation in data-driven sciences. There are also efforts that provide users access to a set of web-based exploratory analysis tools, and report descriptive statistics over datasets, but any new idea, typically not anticipated by data providers, is met with the same barriers. Many scientists aren’t able to innovate for themselves. In this talk, I would argue that programming language community can help bridge this digital divide by invention and refinement of what I call shared data science infrastructures (SDSIs). I will also present three examples of SDSIs in such diverse domains as software analytics, data-driven genomics, and transportation.

Hridesh Rajan is a full professor of computer science at Iowa State University, where he has been since 2005. Professor Rajan earned his MS and Ph.D. from the University of Virginia in 2004 and 2005 respectively. Professor Rajan’s recent research and educational activities are aimed at decreasing the barrier to entry to data-driven sciences to broaden participation. His work on the Boa project is aimed at invention and refinement of cyberinfrastructures that democratize data-driven science. His work on the Midwest Big Data Summer School is experimenting with broadly accessible data science curricula. Professor Rajan was the founding general chair of the Midwest Big Data Summer School. Professor Rajan’s research interests also include programming language design and implementation, and software engineering. He leads two research projects: Panini, whose goals are to enable modular reasoning about concurrent programs, and Boa that was established in Summer 2012 as an end-to-end infrastructure for analyzing large-scale software repositories and other open data sets. Professor Rajan is the director of the Laboratory for Software Design at Iowa State University, director of graduate admissions and recruitment for the computer science department, chair of the curriculum committee for the data science educational programs at Iowa State University, and chair of the information technology committee for the university. Professor Rajan serves on the steering committee of the Midwest Big Data Hub, a consortium of universities in the Midwest region of the United States focussed on promoting data science activities. Professor Rajan is a recipient of the National Science Foundation CAREER award in 2009, LAS Award for Early Achievement in Research in 2010, and a Big-12 Fellowship in 2012. He is a senior member of ACM, and a member of IEEE, and AAAS. He is also the inaugural holder of the Kingland professorship in the Department of Computer Science.

Thu 26 Oct

15:30 - 17:00: SPLASH-I - Machine Learning & Data Science at Regency D
Chair(s): Cristina Cifuentes
splash-2017-SPLASH-I150902460000015:30 - 16:00
splash-2017-SPLASH-I150902640000016:00 - 16:30
splash-2017-SPLASH-I150902820000016:30 - 17:00