Carlos R. Rivero Headshot

Carlos R. Rivero

Associate Professor

Department of Computer Science
Golisano College of Computing and Information Sciences

585-475-2979
Office Location

Carlos R. Rivero

Associate Professor

Department of Computer Science
Golisano College of Computing and Information Sciences

Education

BS in Software Engineering, University of Seville (Spain); MS, Ph.D. in Computer Science, University of Seville (Spain)

Bio

I got my PhD from the University of Seville, Spain in 2012. My advisors were Prof. David Ruiz and Prof. Rafael Corchuelo. During my PhD, I visited Prof. Alberto Pan at the University of A Coruna, Spain, Dr. Paolo Papotti at Roma Tre University, Italy, and Prof. Christian Bizer at Free University of Berlin, Germany. From 2013 to 2015, I worked as a postdoc at the University of Idaho, USA, collaborating with Prof. Hasan Jamil and Prof. H.V. Jagadish. My research interests are related to graph theory and its applications to computer-aided program comprehension, graph databases, and the Web of Data.

585-475-2979

Personal Links
Areas of Expertise

Currently Teaching

CSCI-420
3 Credits
This course provides an introduction to the major concepts and techniques used in data mining of large databases. Topics include the knowledge discovery process; data exploration and cleaning; data mining algorithms; and ethical issues underlying data preparation and mining. Data mining projects, presentations, and a term paper are required.
CSCI-620
3 Credits
This course provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. First, practical techniques used in exploratory data analysis and mining are introduced; topics include data preparation, visualization, statistics for understanding data, and grouping and prediction techniques. Second, approaches used to store, retrieve, and manage data in the real world are presented; topics include traditional database systems, query languages, and data integrity and quality. Case studies will examine issues in data capture, organization, storage, retrieval, visualization, and analysis in diverse settings such as urban crime, drug research, census data, social networking, and space exploration. Big data exploration and management projects, a term paper and a presentation are required. Sufficient background in database systems and statistics is recommended.
CSCI-723
3 Credits
This course starts with an introduction to advanced topics in relational databases, including their implementation and advanced SQL queries. Discussions about benefits and drawbacks of relational databases will arise, which will be the foundation for introducing new types of NoSQL databases; that is, column, key-value, and graph databases. This course will then focus on the rationale, implementation, and storing and querying capabilities of graph databases. Assignments of various kinds will be used to assess individual performance of students. Additionally, the course requires a team-based project in which students will analyze and implement state-of-the-art approaches over graph databases. Teams will present the results of their projects in class.