Data Curation in the Age of Data Science
Wednesday, October 19, 2016
to 5:00 PM
119 Humanities Building
6100 Main St
Houston, Texas, USA
Carlos Monroy is a Research Scientist with the Department of Computer Science at Rice University, working with Dr. Chris Jermaine’s Data Intensive Systems Group. Throughout his career, he has been interested in “sense making,” more specifically in the synergies between computing and socio-technical approaches for advancing discovery. Presently he is part of a multi-institutional research project (The Pliny Project) that aims at storing, curating and analyzing large amounts of programming code (Big Code) in order to improve software quality, productivity and security. He also works on what he calls Learninformatics (term coined during the NSF Big Data Ideas Lab Oct 2013), which can be defined as: An interdisciplinary approach to develop and improve methods for storing, curating, organizing and analyzing learning data.
Previously, as Data Scientist for STEMscopes™, his work focused on learning analytics and the big data generated by nearly half a million students and over 50,000 teachers that used STEMScopes™ an on-line science curriculum. For more than fifteen years, he has worked on numerous interdisciplinary collaborations with domain experts in various disciplines such as education, linguistics, art history and nautical archaeology. Prior to joining Rice University, his research at the Center for the Study of Digital Libraries at Texas A&M contributed to the creation and development of various digital repositories related to literature collections, art history (Pablo Picasso) and maritime archaeology, including a multilingual retrieval system for improving ship reconstruction. His interests include data and text mining, information retrieval and visualization, digital humanities, and socio-technical systems. Carlos received his B.S. from Universidad Rafael Landívar (Guatemala), followed by masters and Ph.D. degrees from Texas A&M University, all in Computer Science.
This event is part of Data Week, http://researchdata.rice.edu/events/