Zhengjie Miao

Ph.D. Student in Computer Science

Duke University

Biography

I am Zhengjie Miao (苗正杰), currently a PhD student in the Department of Computer Science, Duke University. I am working with Prof. Sudeepa Roy and Prof. Jun Yang on databases. Here is my curriculum vitae.

Before joining Duke, I received M.S. in Computer Science from Columbia University, where I’ve worked on interactive data analysis system under the advisory of Prof. Eugene Wu. I got my B.S. in Computer Science from Peking University, under the advisory of Prof. Xiaoru Yuan.

Interests

Database
Data management
Visual Analytics

Education

Ph.D. in Computer Science, 2022(expected)

Duke University
M.S. in Computer Science, 2016

Columbia University
B.S. in Computer Science and Technology, 2015

Peking University

Featured Publications

Amir Gilad*, Zhengjie Miao*, Sudeepa Roy, Jun Yang (2021). Understanding Queries by Conditional Instances. ACM SIGMOD International Conference on Management of Data (SIGMOD) 2022 (to appear).

Yuliang Li, Xiaolan Wang, Zhengjie Miao, Wang-Chiew Tan (2021). Data Augmentation for ML-driven Data Preparation and Integration. Proceedings of the VLDB Endowment (PVLDB), Vol 14, Tutorial.

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Chenjie Li, Zhengjie Miao, Qitian Zeng, Boris Glavic, Sudeepa Roy (2021). Putting Things into Context: Rich Explanations for QueryAnswers using Join Graphs. ACM SIGMOD International Conference on Management of Data (SIGMOD) 2021.

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Zhengjie Miao, Yuliang Li, Xiaolan Wang (2021). Rotom: A Meta-Learned Data Augmentation Framework for Entity Matching, Data Cleaning, Text Classification, and Beyond. ACM SIGMOD International Conference on Management of Data (SIGMOD) 2021.

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Zhengjie Miao, Yuliang Li, Xiaolan Wang, Wang-Chiew Tan (2020). Snippext: Semi-supervised Opinion Mining with Augmented Data. The Web Conference (WWW).

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Zhengjie Miao, Sudeepa Roy, Jun Yang (2019). Explaining Wrong Queries Using Small Examples. ACM SIGMOD International Conference on Management of Data (SIGMOD) 2019.

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Zhengjie Miao*, Qitian Zeng*, Boris Glavic, Sudeepa Roy (2018). Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances. ACM SIGMOD International Conference on Management of Data (SIGMOD) 2019.

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