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portfolio

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publications

Cache me if you can: Accuracy-aware inference engine for differentially private data exploration

Miti Mazmudar, Thomas Humphries, Jiaxiang Liu, Matthew Rafuse, Xi He

VLDB, 2023

[pdf]

JoinBoost: Grow Trees Over Normalized Data Using Only SQL

Zezhou Huang, Rathijit Sen, Jiaxiang Liu, Eugene Wu

VLDB, 2023

[pdf]

Saibot: A Differentially Private Data Search Platform

Zezhou Huang, Jiaxiang Liu, Daniel Alabi, Raul Castro Fernandez, Eugene Wu

VLDB, 2023

[pdf]

The Fast and the Private: Task-based Dataset Search

Zezhou Huang, Jiaxiang Liu, Haonan Wang, Eugene Wu

CIDR, 2023

[pdf]

SET: Searching Effective Supervised Learning Augmentations in Large Tabular Data Repositories

Jiaxiang Liu, Zezhou Huang, Eugene Wu

GUIDE-AI@SIGMOD, 2024

[pdf]

Suna: Scalable Causal Confounder Discovery over Relational Data

Jiaxiang Liu, Eugene Wu

SIGMOD, 2025

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talks

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Tutorial 1 on Relevant Topic in Your Field

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Conference Proceeding talk 3 on Relevant Topic in Your Field

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teaching

COMS W4111 Introduction to Databases

Fall 2024, Columbia Univerity