Dong Xie
Assistant Professor
Department of Computer Science and Engineering
School of Electrical Engineering and Computer Science
Penn State University
Office Address:
W325 Westgate Building
University Park, PA 16802
Email: dongx (at) psu (dot) edu
Phone: (814) 865-9148
I am looking for highly motivated PhD and MS students interested in databases and systems.
Please apply for Penn State CSE Graduate Programs and also feel free to drop me an email.
Bio
Dong Xie is an assistant professor in the computer science and engineering department at Penn State University. He received his Ph.D in Computer Science from University of Utah in 2020, and received his bachelor’s degree from ACM Honored Class of Shanghai Jiao Tong University in 2015. He received the Google Research Scholar Award in 2023, Microsoft Research PhD Fellowship in 2018, and SoCC best paper runner-up in 2019.
His research interest lies in building data systems to address the challenges of processing and analyzing real-world large-scale data. His research span in multiple areas including data systems on modern hardware, distributed databases, main-memory databases, stream processing systems, approximate query processing, spatio-temporal data processing, data privacy, and system security.
You can find a more complete CV here.
Students:
Douglas Rumbaugh, PhD, since Fall 2021.
Maxwell Norfolk, PhD, since Fall 2022.
Selected Publications:
- Towards Systematic Index Dynamization
Douglas Rumbaugh, Dong Xie, Zhuoyue Zhao
In Proceedings of 50th International Conference on Very Large Data Bases (VLDB 2024) - Practical Dynamic Extension for Sampling Indexes
Douglas Rumbaugh, Dong Xie
In Proceedings of 43th ACM SIGMOD International Conference on Management of Data (SIGMOD 2024) - AB-tree: Index for Concurrent Random Sampling and Updates
Zhuoyue Zhao, Dong Xie, Feifei Li
In Proceedings of 48th International Conference on Very Large Data Bases (VLDB 2022) - Towards Practical Oblivious Join
Zhao Chang, Dong Xie, Sheng Wang, Feifei Li
In Proceedings of 41th ACM SIGMOD International Conference on Management of Data (SIGMOD 2022) - SSDs Striking Back: The Storage Jungle and Its Implications on Persistent Indexes
Kaisong Huang, Darien Imai, Tianzheng Wang, Dong Xie
In Proceedings of 2022 Conference on Innovative Data Systems Research (CIDR 2022) - Spatial Independent Range Sampling
Dong Xie, Jeff M. Phillips, Michael Matheny, Feifei Li
In Proceedings of 40th ACM SIGMOD International Conference on Management of Data (SIGMOD 2021) - Efficient Oblivious Query Processing for Range and kNN Queries
Zhao Chang, Dong Xie, Feifei Li, Jeff M. Phillips, Rajeev Balasubramonian
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021 - Scalable Spatial Scan Statistics for Trajectories
Michael Matheny, Dong Xie, Jeff M. Phillips
ACM Transaction on Knowledge Discovery from Data (TKDD), 2020 - Narrowing the Gap Between Serverless and its State with Storage Functions
Tian Zhang, Dong Xie, Feifei Li, Ryan Stutsman
In Proceedings of 10th ACM Symposium of Cloud Computing (ACM SoCC 2019)
Awarded Best Paper Runner-Up - FishStore: Faster Ingestion with Subset Hashing [Code]
Dong Xie, Badrish Chandramouli, Yinan Li, Donald Kossmann
In Proceedings of 38th ACM SIGMOD International Conference on Management of Data (SIGMOD 2019) - Solar: Towards a Shared-Everything Database on Distributed Log-Structured Storage
Tao Zhu, Zhuoyue Zhao, Feifei Li, Weining Qian, Aoying Zhou, Dong Xie, Ryan Stutsman, Haining Li, Huiqi Hu
In Proceedings of 2018 USENIX Annual Technical Conference (USENIX ATC 2018) - Distributed Trajectory Similarity Search [Code]
Dong Xie, Feifei Li, Jeff M. Phillips
In Proceedings of 43rd International Conference on Very Large Data Bases (VLDB 2017) - Oblivious RAM: A Dissection and Experimental Evaluation [Code]
Zhao Chang, Dong Xie, Feifei Li
In Proceedings of 42nd International Conference on Very Large Data Bases (VLDB 2016) - Simba: Efficient In-Memory Spatial Analytics [Code]
Dong Xie, Feifei Li, Bin Yao, Gefei Li, Liang Zhou, Minyi Guo
In Proceedings of 35th ACM SIGMOD International Conference on Management of Data (SIGMOD 2016)