The two keynote speakers at the Oct. 11 College of Liberal Arts and Sciences’ Signature Research Themes workshop, "Exploring Data-Rich Environments," bring exciting perspectives and expertise to the conference.
• Matt Jockers, from the Department of English at the University of Nebraska-Lincoln, speaks at the 1 p.m. program. His talk is titled “Data Driven Criticism: A (Literary) Lab Report.
• Kris de Brabanter, from the departments of Statistics and Computer Science at Iowa State, speaks after dinner at 7 p.m. His lecture is “Challenges in Big Data: Theory and Applications."
The free workshop, at the Scheman Building, will examine new avenues for data-driven research in the sciences, humanities and business by leveraging strengths in the mathematical sciences. The conference is designed for faculty and research staff interested in cross-disciplinary research opportunities. The workshop also includes a panel discussion, breakout sessions and dinner.
Register for the workshop by emailing Kristin Doerder (email@example.com) by noon on Friday, October 4. The workshop’s two keynote lectures are open to everyone, and no registration is required for the lectures. Registration is required for the remainder of the workshop and dinner.
Matt Jockers is a leading researcher in literary text mining and computational text analysis. His publications include Macroanalysis: Digital Methods and Literary History (UIUC Press 2013), as well as many essays on computational text analysis, authorship attribution and literature. Jockers’ research has been profiled in the academic and mainstream press including The New York Times, Nature, the Chronicle of Higher Education, Wired UK, New Scientist, Smithsonian, NBC News, The Financial Times of London and many others. Jockers is a professor of English and Faculty Fellow in the Center for Digital Humanities Research at the University of Nebraska. Prior to that he was a lecturer and academic technology specialist in the Department of English at Stanford where he co-founded the Stanford Literary Lab.
In Macroanalysis: Digital Methods & Literary History, Jockers argues that literary scholars can no longer simply "close read" literature. In this talk, he will discuss and demonstrate how big data is driving, even forcing, new ways of studying literature at the macro scale. He’ll discuss the challenges associated with studying a corpus of 3,500 novels using traditional techniques and then explain how he leveraged machine learning and statistics in order to uncover latent correlations between literary themes, literary representations of place, and the emotions or sentiments most often associated with these places and themes in the literature. His talk will conclude with a demonstration of why close reading is impoverished as a means of studying literary history, and he’ll offer a case study related to Jane Austen’s legacy and the more or less forgotten work of Austen’s literary mentor, Maria Edgeworth.
Kris De Brabanter was born in Ninove, Belgium. He received a master’s degree in electronic engineering in 2005 from the Erasmus Hogeschool Brussel. In 2007 he received a master’s degree in electrical engineering from the Katholieke Universiteit Leuven (Belgium) and in 2011 he obtained a Ph.D. at the same university. He was a postdoctoral researcher at the KU Leuven in the Department of Electrical Engineering. Currently, he is an assistant professor at Iowa State University in the department of statistics and computer science. He is the main developer of the LSSVMLab and StatLSSVM software.
According to De Brabanter, "Since sensors and measurement systems are becoming cheaper each year, industry can produce massive data sets every week. These data sets contain valuable information about the underlying process or mechanism. Unfortunately due to the large size of the data, they are simply stored and barely anything is done with it. In this presentation we shed some light on how to proceed when having large data sets. We will discuss a recent developed method to extract useful information from the data and point out several challenges for the future. But even greater than the challenges are the opportunities that big data presents. McKinsey & Company calls big data ‘the next frontier for innovation, competition and productivity.’ We can answer questions with big data that were beyond reach in the past. We can extract insight and knowledge, identify trends and use the data to improve productivity, gain competitive advantage and create substantial value for the world economy."
1-1:15 p.m. Benton Auditorium – Welcome, Dean Beate Schmittmann, College of Liberal Arts and Sciences
1:15-2:15 p.m. Benton Auditorium – Opening keynote: “Data Driven Criticism: A (Literary) Lab Report,” by Matthew Jockers, Department of English, University of Nebraska-Lincoln
2:15-2:30 p.m. Benton Auditorium – Update on ISU resources for big-data research
2:30-3 p.m. 1st-Floor Lobby – Refreshments
3-4 p.m. 004 Scheman – Panel Discussion
4-5 p.m. 004 Scheman – Breakout sessions
5-5:45 p.m. 1st-Floor Lobby – Social hour: Cash bar, light hors d’oeuvres
5:45-7 p.m. 190 Stagedoor – Buffet dinner
7-8 p.m. 190 Stagedoor – Closing keynote: “Challenges in Big Data: Theory and Applications,” by Kris de Brabanter, departments of Computer Science and Statistics, Iowa State University