Welcome!
I am a final year PhD student at MIT in the computer science (EECS) department where I am very fortunate to be advised by Julian Shun. I am also currently a student researcher at Google Research, where I work with Jakub Łącki on the Graph Mining team.
I got my B.S. from Cornell University with a double major in Computer Science and Operations Research, where I had the honor of being advised by Austin R. Benson, David Shmoys, and Jamol Pender.
Research Interests: parallel algorithms, clustering algorithms, graph algorithms, dynamic algorithms
Papers
- Shangdi Yu, Julian Shun, “Parallel Filtered Graphs for Hierarchical Clustering”, Proceedings of the IEEE International Conference on Data Engineering (ICDE), pp. 1967-1980. 2023
- Shangdi Yu, Horace He, “Transcending Runtime-Memory Tradeoffs in Checkpointing by being Fusion Aware”, Proceedings of Machine Learning and Systems 5 (MySys). 2023
- Michael Huang, Shangdi Yu, and Julian Shun “Faster Parallel Exact Density Peaks Clustering”, Proceedings of the SIAM Conference on Applied and Computational Discrete Algorithms (ACDA), pp. 49-62. 2023. (Best Student Presentation Award)
- Quanquan Liu, Jessica Shi, Shangdi Yu, Laxman Dhulipala, and Julian Shun, “Parallel Batch-Dynamic Algorithms for k-Core Decomposition and Related Graph Problems”, Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), pp.191–204, 2022 (Best Paper Award)
- Laxman Dhulipala, Quanquan Liu, Sofya Raskhodnikova, Jessica Shi, Julian Shun, and Shangdi Yu, “Differential Privacy from Locally Adjustable Graph Algorithms: k-Core Decomposition, Low Outdegree Ordering, and Densest Subgraphs”, Proceedings of the IEEE Symposium on Foundations of Computer Science (FOCS), pp. 754-765, 2022.
- Yiqiu Wang, Rahul Yesantharao, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun, “ParGeo: A Library for Parallel Computational Geometry”, Proceedings of the European Symposium on Algorithms (ESA), pp. 88:1-88:19, 2022.
- Yiqiu Wang, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun, “POSTER: ParGeo: A Library for Parallel Computational Geometry”, Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), pp.450-452, 2022.
- Shangdi Yu, Yiqiu Wang, Yan Gu, Laxman Dhulipala, Julian Shun, “ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain”, Proceedings of the VLDB Endowment 15, 2, pp. 285–298, 2021
- Yiqiu Wang, Shangdi Yu, Yan Gu, and Julian Shun, “Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering”, Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pp. 1982-1995. 2021.
- Yiqiu Wang, Shangdi Yu, Yan Gu, and Julian Shun, “A Parallel Batch-Dynamic Data Structure for the Closest Pair Problem”, Proceedings of the International Symposium on Computational Geometry (SoCG), pp. 60:1-60:16, 2021.
- Yiqiu Wang, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun, “GeoGraph: A Framework for Graph Processing on Geometric Data”, ACM SIGOPS Operating Systems Review (OSR), Vol. 55 Issue 1, pp. 38-46, 2021.
- Laxman Dhulipala, Quanquan Liu, Julian Shun, and Shangdi Yu, “Parallel Batch-Dynamic k-Clique Counting”, Proceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), pp.129–143, 2021
- Xiang Fu, Shangdi Yu, and Austin R. Benson, “Modelling and Analysis of Tagging Networks in Stack Exchange Communities”, Journal of Complex Networks 8, no.5, 2020
Talks and Presentations
- ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain
- International Conference on Very Large Data Bases (VLDB)
- Algorithm Engineering course at MIT
- University of Washington
- Capital Area Theory Seminar (CATS) at University of Maryland
- Stanford Systems Seminar
- University of California, Berkeley
- Data Science Seminar at University of Utah
- Parallel Batch-Dynamic k-Clique Counting
- SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS)
- POSTER: ParGeo: A Library for Parallel Computational Geometry
- The Applications Driving Architectures Center (ADA) Symposium
- Parallel Filtered Graphs for Hierarchical Clustering
- IEEE International Conference on Data Engineering (ICDE)
- Faster Parallel Exact Density Peaks Clustering
- SIAM Conference on Applied and Computational Discrete Algorithms (ACDA)
Service
- Program Committee Member: SDM2024, GRADES-NDA (SIGMOD23 Workshop), DRAGSTERS (PLDI23 Workshop)
- Conference Reviewer: ALENEX2024, SOSA2024, HPEC2023, KDD2023, ACDA2023, PPoPP2023, SPAA2022, SEA2022, ALENEX2022, PPoPP2022, ACDA2021, HiPC2021, IPDPS2021, ICDCS2021, SPAA2021, Euro-Par2020, ESA2020
- Journal Reviewer: TKDE, PLOS ONE, JEA, TOPC, TOMS
Intern
I interned at Meta’s PyTorch Compiler Team in summer 2022!
I interned at the New York Times in summer 2018!
Awards
- Two Sigma Diversity PhD Fellowship Finalist, 2022
- Siebel Scholar, Class of 2022
- MIT EECS Department, Edwin S. Webster Graduate Fellowship 2019
- Cornell University, Computer Science Prize for Academic Excellence and Leadership 2019
- Cornell University, Operations Research Prize for Academic Excellence 2019
Teaching
I was a teaching assistant for the following courses.
MIT:
6.046: Design and Analysis Algorithms
Cornell:
CS 4780: Machine Learning for Intelligent Systems
CS 1110: Introduction to Computing Using Python
CS 4852: Networks II: Market Design