scalable parallel algorithms, parallel graph processing for static, dynamic, and streaming graphs.

email: laxman [at] umd.edu

CV --
GitHub --
Hobbies

I am an Assistant Professor in the Department of Computer Science at the University of Maryland, College Park, and a research scientist at Google Research with the Graph Mining team.

I obtained my Ph.D. from Carnegie Mellon University, where I was advised by Guy Blelloch, and was a postdoc at MIT with Julian Shun.

I am broadly interested in efficient parallel algorithms, e.g., for
parallel clustering and parallel graph processing. I am also
interested in models of parallel computation motivated by emerging
hardware and exploring these models theoretically and practically.

- F23: CMSC451: Design and Analysis of Computer Algorithms
- S23: CMSC858N: Scalable Parallel Algorithms and Data Structures
- F22: CMSC451: Design and Analysis of Computer Algorithms

[arxiv]

Laxman Dhulipala, Jason Lee, Jakub Łącki, and Vahab Mirrokni

To appear in SIGMOD 2024.

[pdf]

Hongbo Kang, Yiwei Zhao, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, Charles McGuffey and Phillip B. Gibbons

Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2023.

[pdf] [arxiv]

Xiaojun Dong, Yunshu Wu, Zhongqi Wang, Laxman Dhulipala, Yan Gu, and Yihan Sun

Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2023.

[arxiv]

Yuyang Xie, Jiezhong Qiu, Laxman Dhulipala, Wenjian Yu, Jie Tang, Richard Peng, and Chi Wang

IEEE Transactions on Knowledge and Data Engineering, 2023.

[arxiv]

Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirronki, and Jessica Shi

Conference on Neural Information Processing Systems (NeurIPS), 2022.

[arxiv]

Hongbo Kang, Yiwei Zhao, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, Charles McGuffey and Phillip B. Gibbons

Proceedings of the VLDB Endowment, 2022.

Best Paper Runner Up

[arxiv]

Laxman Dhulipala, Quanquan C. Liu, Sofya Raskhodnikova, Jessica Shi, Julian Shun, and Shangdi Yu

Proceedings of the IEEE Symposium on Foundations of Computer Science (FOCS), 2022.

[arxiv]

Yiqiu Wang, Rahul Yesantharao, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun

Proceedings of the European Symposium on Algorithms (ESA), 2022.

[pdf]

Quanquan Liu, Jessica Shi, Shangdi Yu, Laxman Dhulipala, and Julian Shun

Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2022.

Best Paper Award

[pdf] [arxiv]

Jessica Shi, Laxman Dhulipala, and Julian Shun

Proceedings of the VLDB Endowment, 2022.

[pdf] [code]

Laxman Dhulipala, Guy E. Blelloch, Yan Gu, and Yihan Sun

ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2022.

[pdf] [arxiv]

Jessica Shi, Laxman Dhulipala, and Julian Shun

Proceedings of the VLDB Endowment, 2022.

[pdf] [arxiv]

Shangdi Yu, Yiqiu Wang, Yan Gu, Laxman Dhulipala, and Julian Shun

To appear in Proceedings of the VLDB Endowment, 2022.

[pdf] [code]

Daniel Anderson, Guy E. Blelloch, Laxman Dhulipala, Magdalen Dobson, and Yihan Sun

Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2022.

[pdf] [code]

Yiqiu Wang, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun

Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 2022.

[pdf] [arxiv]

Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirronki, and Jessica Shi

Proceedings of the International Conference on Machine Learning (ICML), 2021.

[pdf] [arxiv] [code]

Jessica Shi, Laxman Dhulipala, David Eisenstat, Jakub Łącki, and Vahab Mirrokni

Proceedings of the VLDB Endowment (PVLDB), 2021.

[pdf] [arxiv] [code]

Jessica Shi, Laxman Dhulipala, and Julian Shun

Proceedings of the SIAM Conference on Applied and Computational Discrete Algorithms (ACDA), 2021.

[pdf]

Hongbo Kang, Phillip B. Gibbons, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, and Charles McGuffey

Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2021.

[pdf] [code]

Yiqiu Wang, Shangdi Yu, Laxman Dhulipala, Yan Gu, and Julian Shun

ACM SIGOPS Operating Systems Review, 2021

[pdf] [code]

Jiezhong Qiu, Laxman Dhulipala, Jie Tang, Richard Peng, and Chi Wang

Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 2021.

[pdf] [arxiv] [code]

Tom Tseng, Laxman Dhulipala, and Julian Shun

Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), 2021.

[pdf] [arxiv] [code]

Laxman Dhulipala, Changwan Hong, and Julian Shun

Proceedings of the VLDB Endowment (PVLDB), 2021.

[pdf] [arxiv]

Laxman Dhulipala, Quanquan Liu, Julian Shun, and Shangdi Yu

Proceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), 2021.

[pdf]

Guy Blelloch, Laxman Dhulipala, Phillip Gibbons, Yan Gu, Charles McGuffey, and Julian Shun

Proceedings of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS), 2021.

[pdf] [arxiv] [Google AI Blog Post]

Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Łącki, Vahab Mirrokni, and Warren Schudy

Proceedings of the VLDB Endowment (PVLDB), 2020. (To be presented at VLDB'21)

[pdf] [arxiv]

Changwan Hong, Laxman Dhulipala, and Julian Shun

Proceedings of International Conference on Parallel Architectures and Compilation Techniques (PACT), 2020.

[pdf] [arxiv] [code]

Laxman Dhulipala, Charles McGuffey, Hongbo Kang, Yan Gu, Guy Blelloch, Phillip Gibbons, and Julian Shun

Proceedings of the VLDB Endowment (PVLDB), 2020.

Memorable Paper Award Finalist at the Non-Volatile Memories Workshop (NVMW’20)

[pdf] [code]

Laxman Dhulipala, Jessica Shi, Tom Tseng, Guy E. Blelloch, and Julian Shun

Proceedings of the Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), 2020

[pdf] [code]

Guy E. Blelloch, Daniel Anderson, and Laxman Dhulipala

Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2020.

[pdf] [arxiv] [code]

Yunming Zhang, Ajay Brahmakshatriya, Xinyi Chen, Laxman Dhulipala, Shoaib Kamil, Saman Amarasinghe, and Julian Shun

Proceedings of the International Symposium on Code Generation and Optimization (CGO), 2020.

[pdf] [arxiv]

Laxman Dhulipala, David Durfee, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, and Xiaorui Sun

Proceedings of the ACM-SIAM Symposium on Discrete Algorithms (SODA), 2020.

[pdf] [arxiv]

Umut Acar, Daniel Anderson, Guy Blelloch, Laxman Dhulipala, and Sam Westrick

Proceedings of the European Symposium on Algorithms (ESA), 2020.

[pdf] [arxiv]

Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Łącki, and Vahab Mirrokni

Proceedings of the IEEE Symposium on Foundations of Computer Science (FOCS), 2019.

[pdf] [arxiv] [code]

Laxman Dhulipala, Guy Blelloch, and Julian Shun

Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), 2019.

Distinguished Paper Award

[pdf] [arxiv]

Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari, Jakub Łącki, Vahab Mirrokni, and Warren Schudy

Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2019.

Invited to Special Issue

[pdf] [arxiv]

Umut Acar, Daniel Anderson, Guy Blelloch, and Laxman Dhulipala

Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2019.

[pdf] [arxiv] [code]

Thomas Tseng, Laxman Dhulipala, and Guy Blelloch

Proceedings of the SIAM Meeting on Algorithm Engineering and Experiments (ALENEX), 2019.

[pdf] [arxiv] [code]

Laxman Dhulipala, Guy Blelloch, and Julian Shun

Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2018.

Best Paper Award

Invited to Special Issue

[pdf] [code]

Laxman Dhulipala, Guy Blelloch, and Julian Shun

Proceedings of the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 2017.

[pdf] [arxiv]

Laxman Dhulipala, Igor Kabiljo, Brian Karrer, Giuseppe Ottaviano, Sergey Pupyrev, and Alon Shalita

Proceedings of the ACM Conference on Knowledge Discovery and Data Mining (KDD), 2016.