Published in IEEE DataCom, 2019
This paper introduces VCNE, a network embedding approach for very large graphs. 
Recommended citation: S. Riazi and B. Norris. Distributed-memory vertex-centric network embedding for large-scale graphs. Proceedings of the 2019 IEEE 5th International Conference on Big Data Intelligence and Computing (DATACOM), Taiwan, 2019 http://sarariazi.github.io/files/vcne.pdf
Published in IEEE Big Data, 2018
This paper introduces novel algorithms for computing SSSP over very large dynamic graphs using a vertex-centric approach. 
Recommended citation: S. Riazi, S. Srinivasan, S. K. Das, S. Bhowmick and B. Norris, Single-Source Shortest Path Tree for Big Dynamic Graphs, 2018 IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, 2018, pp. 4054-4062. http://sarariazi.github.io/files/sssp.pdf
Published in IEEE Big Data, 2016
This paper introduces GraphFlow framework for processing big graphs using Galaxy and Apache Spark. 
Recommended citation: S. Riazi and B. Norris, GraphFlow: Workflow-Based Big Graph Processing, In Proc. of 2016 IEEE International Conference on Big Data (Big Data), 2016. https://hpcl.cs.uoregon.edu/pubs/biggraphs16.pdf