Opetusnäyte apulaisprofessorin tehtävään: Principles of data management: from relational systems to big data

Event type: 
Lecture
Event time: 
11.09.2014 - 10:15 - 10:45
Lecturer : 
Julia Stoyanovich
Place: 
C220
Description: 

Apulaisprofessori Julia Stoyanovich (Drexel University, USA) on hakenut tietojenkäsittelytieteen (erityisesti tiedonhallinnan) apulaisprofessorin tehtävää ja antaa julkisen opetusnäytteensä aiheesta "Principles of data management: from relational systems to big data" torstaina 11.9.2014 klo 10:15 salissa C220. Tervetuloa!

Abstract

In this talk I will discuss the fundamental principles that drive research and practice in data management.   These principles  make our field beautiful and practical, allow us to respond to the ever-changing demands of the information ecosystem, and have impact far beyond our field.  They are the reason that every Computer Science student should take a data management course.

Bio

Julia Stoyanovich is an Assistant Professor of Computer Science at the College of Computing and Informatics at Drexel University (Philadelphia, USA). Prior to joining Drexel, she was a Postdoctoral researcher and an NSF/CRA Computing Innovations Fellow at the University of Pennsylvania. Julia received her MS and PhD degrees in Computer Science at Columbia University (New York, USA) in 2003 and 2009, respectively, and her BS in Computer Science and in Mathematics and Statistics at the University of Massachusetts Amherst, USA in 1998. Having graduated from college, Julia spent 5 years in the start-up industry, as a software developer, data architect and database administrator. This experience has motivated her to work with real datasets whenever possible, and to deliver results of her research to the communities of target users, as part of open-source systems or as stand-alone prototypes.

Julia's research is in the area of data and knowledge management. Her focus is on developing novel information discovery approaches, with the goal of helping the user identify relevant information, and ultimately transform that information into knowledge. She has recently worked with a wide variety of real datasets, from shopping, dating and collaborative tagging applications, to full-genome association studies and gene expression microarrays, to data-intensive workflows and scientific articles.  Additional information about her research is available at http://cci.drexel.edu/faculty/jstoy/.

 

08.09.2014 - 10:52 Jukka Paakki
08.09.2014 - 10:52 Jukka Paakki