Hi! I obtained my PhD at the David R. Cheriton School of Computer Science at the University of Waterloo.
I researched graph processing systems with Prof. Semih Salihoglu as part of the Data Systems Group.
I am excited about highly scalable data processing systems. In my research, I showed how differential computation can be a great fit for building graph processing systems that benefit from incrementally sharing computations.
Optimizing Differential Computation for Large-Scale Graph Processing. Siddhartha Sahu. Ph.D. Thesis, University of Waterloo, 2024.
[Publication: thesis]
Optimizing Differentially-Maintained Recursive Queries on Dynamic Graphs. Khaled Ammar, Siddhartha Sahu, Semih Salihoglu, and M. Tamer Özsu. PVLDB, 2022.
Graphsurge: Graph Analytics on View Collections Using Differential Computation. Siddhartha Sahu and Semih Salihoglu. ACM SIGMOD, 2021.
The Ubiquity of Large Graphs and Surprising Challenges of Graph Processing: Extended Survey. Siddhartha Sahu, Amine Mhedhbi, Semih Salihoglu, Jimmy Lin, and M. Tamer Özsu. The VLDB Journal, 2020.
[Publication: springer.com, manuscript]
Sift: Resource-efficient Consensus with RDMA. Mikhail Kazhamiaka, Babar Memon, Chathura Kankanamge, Siddhartha Sahu, Sajjad Rizvi, Bernard Wong, and Khuzaima Daudjee. CoNEXT, 2019.
[Publication: acm.org]
The Ubiquity of Large Graphs and Surprising Challenges of Graph Processing. Siddhartha Sahu, Amine Mhedhbi, Semih Salihoglu, Jimmy Lin, and M. Tamer Özsu. PVLDB, 2017.
[VLDB 2018 Best Paper]
[Publication: pdf] [Presentation: pdf, slides] [Poster: pdf, slides]
Graphflow: An Active Graph Database (Demo). Chathura Kankanamge, Siddhartha Sahu, Amine Mhedhbi, Jeremy Chen, and Semih Salihoglu. In ACM SIGMOD, 2017.
Graph Mining in Rust, Rust KW Meetup, June 2018.
Managing Connections with Graphs: Uses and Challenges, Starcon, January 2018.
Graphflow: An Active Graph Database & The Ubiquity of Large Graphs and Surprising Challenges of Graph Processing, Invited talk at IIT Bombay & BIT Mesra, December 2017.