| 2025 | ESA | Near-Optimal Differentially Private Graph Algorithms via the Multidimensional AboveThreshold Mechanism. | Laxman Dhulipala, Monika Henzinger, George Z. Li, Quanquan C. Liu, A. R. Sricharan, Leqi Zhu |
| 2025 | SPAA | Dataflow-Specific Algorithms for Resource-Constrained Scheduling and Memory Design. | Abhishek Bhattacharjee, Quanquan C. Liu, Rajit Manohar, Raghavendra Pradyumna Pothukuchi, Muhammed Ugur |
| 2024 | ALENEX | Practical Parallel Algorithms for Near-Optimal Densest Subgraphs on Massive Graphs. | Pattara Sukprasert, Quanquan C. Liu, Laxman Dhulipala, Julian Shun |
| 2024 | COLT | The Predicted-Updates Dynamic Model: Offline, Incremental, and Decremental to Fully Dynamic Transformations. | Quanquan C. Liu, Vaidehi Srinivas |
| 2024 | PODC | Brief Announcement: Improved Massively Parallel Triangle Counting in O(1) Rounds. | Quanquan C. Liu, C. Seshadhri |
| 2024 | PPoPP | Parallel k-Core Decomposition with Batched Updates and Asynchronous Reads. | Quanquan C. Liu, Julian Shun, Igor Zablotchi |
| 2023 | ICALP | Triangle Counting with Local Edge Differential Privacy. | Talya Eden, Quanquan C. Liu, Sofya Raskhodnikova, Adam Smith |
| 2022 | FOCS | Differential Privacy from Locally Adjustable Graph Algorithms: k-Core Decomposition, Low Out-Degree Ordering, and Densest Subgraphs. | Laxman Dhulipala, Quanquan C. Liu, Sofya Raskhodnikova, Jessica Shi, Julian Shun, Shangdi Yu |
| 2022 | STACS | Scheduling with Communication Delay in Near-Linear Time. | Quanquan C. Liu, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang |
| 2022 | SPAA | Parallel Batch-Dynamic Algorithms for k-Core Decomposition and Related Graph Problems. | Quanquan C. Liu, Jessica Shi, Shangdi Yu, Laxman Dhulipala, Julian Shun |
| 2021 | FUN | Tatamibari Is NP-Complete. | Aviv Adler, Jeffrey Bosboom, Erik D. Demaine, Martin L. Demaine, Quanquan C. Liu, Jayson Lynch |
| 2020 | SPAA | Closing the Gap Between Cache-oblivious and Cache-adaptive Analysis. | Michael A. Bender, Rezaul Alam Chowdhury, Rathish Das, Rob Johnson, William Kuszmaul, Andrea Lincoln, Quanquan C. Liu, Jayson Lynch, Helen Xu |
| 2019 | ESA | Structural Rounding: Approximation Algorithms for Graphs Near an Algorithmically Tractable Class. | Erik D. Demaine, Timothy D. Goodrich, Kyle Kloster, Brian Lavallee, Quanquan C. Liu, Blair D. Sullivan, Ali Vakilian, Andrew van der Poel |
| 2018 | SPAA | Red-Blue Pebble Game: Complexity of Computing the Trade-Off between Cache Size and Memory Transfers. | Erik D. Demaine, Quanquan C. Liu |
| 2018 | SPAA | Cache-Adaptive Exploration: Experimental Results and Scan-Hiding for Adaptivity. | Andrea Lincoln, Quanquan C. Liu, Jayson Lynch, Helen Xu |
| 2018 | TCC | Static-Memory-Hard Functions, and Modeling the Cost of Space vs. Time. | Thaddeus Dryja, Quanquan C. Liu, Sunoo Park |
| 2017 | GD | Upward Partitioned Book Embeddings. | Hugo A. Akitaya, Erik D. Demaine, Adam Hesterberg, Quanquan C. Liu |
| 2017 | WADS | Inapproximability of the Standard Pebble Game and Hard to Pebble Graphs. | Erik D. Demaine, Quanquan C. Liu |
| 2015 | RecSys | Kibitz: End-to-End Recommendation System Builder. | Quanquan C. Liu, David R. Karger |
| 2015 | WADS | Polylogarithmic Fully Retroactive Priority Queues via Hierarchical Checkpointing. | Erik D. Demaine, Tim Kaler, Quanquan C. Liu, Aaron Sidford, Adam Yedidia |