This is a personal blog of Shuo Liu (刘硕). I’m currently (2019-) a PhD student in computer science at Georgetown University, studying Byzantine fault-tolerant distributed systems for optimization, advised by Prof. Nitin Vaidya. Prior to this, I was a master student at Georgetown in CS (2017-2019), and bachelor student at Fudan University in mathematics (2013-2017).

During my master’s degree, My advisor was Prof. Lisa Singh, with the help of whom I graduated with thesis “Understanding Relational Background Knowledge Attacks on Social Media”. We studied privacy concerns of social media users, specifically web footprints that users may leave on websites unintentionally, using data scince approaches.

The title of my undergraduate thesis is “Estimation of sparse graph with lifecycle”. My advisor was Prof. Yun Xiong at Fudan University.

My given name in chinese 硕 consists of two parts, 石 (sounds Shi, meaning “stone”) and 页 (meaning “page”). 石 shares the same sound with 十 (meaning “ten”), and from these I get my online nickname “tenpages”. (Yeah I know it’s a little confusing.) (And yeah I have also considered something like “stone page”.)


Find me on dblp and Google Scholar.

Conference papers

  1. Shuo Liu, Nirupam Gupta, and Nitin H. Vaidya. Approximate Byzantine Fault-Tolerance in Distributed Optimization. In Proceedings of the 2021 ACM Symposium on Principles of Distributed Computing (PODC’21). Association for Computing Machinery, New York, NY, USA, 379–389. DOI: 10.1145/3465084.3467902. (Talk)
  2. Nirupam Gupta, Shuo Liu, and Nitin H Vaidya. Byzantine fault-tolerant distributed machine learning with norm-based comparative gradient elimination. In 2021 51th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), IEEE, 2021. (Talk)
  3. Shuo Liu, Lisa Singh, and Kevin Tian. Information exposure from relational background knowledge on social media. In 2020 IEEE International Conference on Data Science and Advanced Analytics (DSAA), pages 282–291, 2020, doi: 10.1109/DSAA49011.2020.00041.


  1. Shuo Liu. A Survey on Fault-tolerance in Distributed Optimization and Machine Learning. arXiv preprint arXiv:2106.08545, 2021.
  2. Shuo Liu, Nirupam Gupta, and Nitin H Vaidya. Asynchronous Distributed Optimization with Redundancy in Cost Functions. arXiv preprint arXiv:2106.03998, 2021.
  3. Shuo Liu, Nirupam Gupta, and Nitin H Vaidya. Approximate Byzantine fault-tolerance in distributed optimization. arXiv preprint arXiv:2101.09337, 2021.
  4. Nirupam Gupta, Shuo Liu, and Nitin H Vaidya. Byzantine fault-tolerant distributed machine learning using stochastic gradient descent (SGD) and norm-based comparative gradient elimination (CGE). arXiv preprint arXiv:2008.04699, 2020.