Carlos R. Rivero Osuna Headshot

Carlos R. Rivero Osuna

Assistant Professor
Department of Computer Science
Golisano College of Computing and Information Sciences

Office Location

Carlos R. Rivero Osuna

Assistant Professor
Department of Computer Science
Golisano College of Computing and Information Sciences


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


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.


Areas of Expertise

Currently Teaching

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.
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.

Select Scholarship

Published Conference Proceedings
Marin, Victor J. and Carlos R. Rivero. "Clustering Recurrent and Semantically Cohesive Program Statements in Introductory Programming Assignments." Proceedings of the 28th ACM International Conference on Information and Knowledge Management. Ed. Wenwu Zhu, Dacheng Tao, Xueqi Cheng, Peng Cui, Elke A. Rundensteiner, David Carmel, Qi He, Jeffrey Xu Yu. Beijing, China: ACM, Web.
Borrego, Agustín, et al. "Generating Rules to Filter Candidate Triples for their Correctness Checking by Knowledge Graph Completion Techniques." Proceedings of the 10th International Conference on Knowledge Capture. Ed. Mayank Kejriwal, Pedro A. Szekely, Raphaël Troncy. Marina del Rey, CA: ACM, Web.
Ayala, Daniel, et al. "AYNEC: All You Need for Evaluating Completion Techniques in Knowledge Graphs." Proceedings of the Semantic Web, 16th International Conference. Ed. Pascal Hitzler, Miriam Fernández, Krzysztof Janowicz, Amrapali Zaveri, Alasdair J. G. Gray, Vanessa López, Armin Haller, Karl Hammar. Portorož, Slovenia: Springer, 2019. Web.
Marin, Victor J. and Carlos R. Rivero. "Towards a Framework for Generating Program Dependence Graphs from Source Code." Proceedings of the 4th ACM SIGSOFT International Workshop on Software Analytics. Ed. Olga Baysal, Tim Menzies. Orlando, Florida: ACM, Web.
Marin, Victor J., et al. "Automated Personalized Feedback in Introductory Java Programming MOOCs." Proceedings of the IEEE 33rd International Conference on Data Engineering (ICDE). Ed. ICDE. San Diego, California: IEEE, 2017. Web.
Nunez, Wilberto Z., Victor J. Marin, and Carlos R. Rivero. "ARCC: Assistant for Repetitive Code Comprehension." Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering. Ed. SEC/FSE. Padderborn, Germany: ACM, 2017. Web.
Jamil, Hasan M. and Carlos R. Rivero. "A Novel Model for Distributed Big Data Service Composition Using Stratified Functional Graph Matching." Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics. Amantea, Italy: ACM Digital Library, 2017. Web.
Jagadeesan, Yogesh, Peizhao Hu, and Carlos R. Rivero. "PLOMaR: An Ontology Framework for Context Modeling and Reasoning on Crowd-sensing Platform." Proceedings of the PerCom Workshops. Ed. ?. Sydney, -: n.p., Web.
Cimmino, Andrea, Carlos R. Rivero, and David Ruiz. "Improving Link Specifications using Context-Aware Information." Proceedings of the LDOW@WWW. Ed. ?. Montreal, -: n.p., Web.
Journal Paper
Hernández, Inma, Carlos R. Rivero, and David Ruiz. "Deep Web Crawling: A Survey." World Wide Web 22. 4 (2019): 1577-1610. Web.
Rivero, Carlos R. and Hasan M. Jamil. "Efficient and Scalable Labeled Subgraph Matching Using SGMatch." Knowledge and Information Systems 51. 1 (2017): 61-87. Print.
Rivero, Carlos R., et al. "Mapping RDF Knowledge Bases Using Exchange Samples." Knowl.-Based Syst.. (2016): 47-66. Web.
Hernández, Inma, et al. "CALA: ClAssifying Links Automatically based on their URL." Journal of Systems and Software. (2016): 130-143. Web.
Rivero, Carlos R., et al. "Discovering and Analysing Ontological Models From Big RDF Data." Journal of Database Management 26. 2 (2015): 48-61. Print.
Rivero, Carlos R., et al. "MostoDEx: A Tool to Exchange RDF Data Using Exchange Samples." Journal of Systems and Software 100. (2015): 67-79. Print.