Yuan Qiu
HELLO!
I am currently a postdoctoral fellow supervised by Prof. Ke Yi. My research interest lies in database theory and systems; data security and privacy; and data sketching. I received my M.Phil. and Ph.D. from the Department of Computer Science and Engineering at The Hong Kong University of Science and Technology (HKUST), under the supervision of Prof. Ke Yi. Prior to that, I received my B.Sc. in Mathematics and Economics, and in Computer Science with First Class Honors from HKUST.
Publications
[DBLP] [ORCID] [Google Scholar] [Semantic Scholar]
- Yuan Qiu and Ke Yi. "Differential Privacy on Dynamic Data." Submitted, 2024.
- Ziyue Huang, Yuan Qiu, Ke Yi, and Graham Cormode. "Frequency Estimation Under Multiparty Differential Privacy: One-shot and Streaming." International Conference on Very Large Databases (VLDB), September 2022. [PDF]
- Yuan Qiu, Wei Dong, Ke Yi, Bin Wu and Feifei Li. "Releasing Private Data for Numerical Queries." ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), August 2022. [PDF]
- Yuan Qiu, Yilei Wang, Ke Yi, Feifei Li, Bin Wu and Chaoqun Zhan. "Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries." ACM SIGMOD International Conference on Management of Data (SIGMOD), June 2021. [PDF] [Full Version]
- Yuan Qiu, Serafeim Papadias and Ke Yi. "Streaming HyperCube: A Massively Parallel Stream Join Algorithm." International Conference on Extending DataBase Technology (EDBT), March 2019. Short paper. [PDF] [Poster]
Work Experience
-
Postdoctoral Fellow, HKUST, Hong Kong SAR, China.
January 2024 - Present
- Keywords: Differential Privacy, Federated Learning, Query Processing.
- Researched on problems related to secure and private query processing.
-
Big Data Engineer, ByteDance, Hangzhou, China.
September 2022 - September 2023
- Keywords: Query Optimization, Distributed Databases, Workload Analysis.
- Languages: C++, Java, Scala. [sample code]
- Worked on feature development for ByteHouse, a commercial version of the ClickHouse database system.
- Researched on cross-platform workload analysis and diagnosis, and implemented prototypes for query pattern finding and accelerating.
- Implemented row-store feature for E-MapReduce Serveless StarRocks product.
-
Intern Engineer, Alibaba Group, Hangzhou, China.
April 2021 - August 2021
- Keywords: Query Optimization, AI4DB, Data Sketching.
- Languages: Java, Python.
- Implemented data sketching algorithms into AnalyticDB database optimizer.
- Researched on database optimization problems, including AI-based query optimization and adaptive query optimization through feedbacks.
-
Intern Engineer, Alibaba Group, Hangzhou, China.
January 2019 - May 2019
- Keywords: Query Optimization, Data Sketching, Approximate Query Processing.
- Languages: Java, C++.
- Implemented approximate query processing algorithms into AnalyticDB database optimizer.
- Researched on cardinality estimation problems, including join size estimation and distinct value counting.
Teaching Experience
-
Teaching Assitant for COMP 3711H, Honors Design and Analysis of Algorithms, Undergraduate level, HKUST.
Fall 2017, Spring 2018, Fall 2018
-
Teaching Assitant for MSBD 5003, Big Data Computing, Graduate Level, HKUST.
Fall 2019, Fall 2020
-
Teaching Assitant for COMP 2711, Discrete Mathematical Tools for Computer Science, Undergraduate Level, HKUST.
Spring 2022
-
Teaching Assitant for Information Systems and Big Data, SZ-HK Collaborative Innovation Research Institude, HKUST.
Summer 2022
-
Teaching Assitant for Basics of Cloud Computing and Big Data, SZ-HK Collaborative Innovation Research Institude, HKUST.
February 2022
-
Teaching Assitant for Big Data Computing with Hadoop and Spark, Harbour Education.
Summer 2021
-
Math Tutor, Math Department, HKUST.
Fall 2015
