Johes Bater

I am a Ph.D. candidate in Computer Science at Northwestern University. Before that, I completed my B.S. and M.S. in Electrical Engineering at Stanford University. Under the guidance of Prof. Jennie Rogers, I research how to implement privacy and security in federated databases. By investigating the intersection of security, privacy, and performance, I hope to build fast, accurate database systems that support privacy-preserving analytics with provable security guarantees.


VaultDB: A Private Data Federation

For many people seeking actionable insights from data, their first major obstacle is getting access to relevant datasets. Despite the abundance of information we collect on practically every domain of life, much of it is fractured among many private data stores. For example, electronic health records on a given patient are often partitioned among multiple hospitals. Querying fractured datasets is often challenging owing to regulatory requirements and privacy concerns. A private data federation (PDF) queries the union of the private records of multiple autonomous data stores such that no one learns about the data of its peers. VaultDB, our PDF prototype, translates SQL queries into secure multi-party computation protocols and orchestrates their execution among the data providers. These cryptographic protocols incur substantial overhead for PDF queries with runtimes typically three or more orders of magnitude slower than that of an insecure execution of the same query. We are researching a query optimizer for VaultDB that leverages properties of the relational model to enable PDF queries to run efficiently. Papers: [pdf], [pdf], Code: [github]

Selected Publications

J. Rogers, J. Bater, X. He, A. Machanavajjhala, M. Suresh, and X. Wang. "Privacy Changes Everything," in POLY Workshop at VLDB, pages 96-111, 2019. [pdf] [slides]

J. Bater, X. He, W. Ehrich, A. Machanavajjhala, and J. Rogers. "Shrinkwrap: Efficient SQL Query Processing in Differentially Private Data Federations," PVLDB, 12(3), 2018. [pdf]

J. Bater, G. Elliott, C. Eggen, S. Goel, A. Kho, and J. Rogers, "SMCQL: Secure Querying for Federated Databases," in PVLDB, 10(6), pages 673-684, 2017. [pdf] [code] [slides]

Invited Talks

"Shrinkwrap: Efficient SQL Query Processing in Differentially Private Data Federations," VLDB, August 2019.

"Differentially Private Query Processing Private Data Federations," Simons Institue for the Theory of Computing, October 2018.

"Shrinkwrap: Efficient SQL Query Processing in Differentially Private Data Federations," University of Wisconsin Database Group, December 2018.

"Differentially Private Query Processing Private Data Federations," Duke University Database Group, October 2018.

"SMCQL: Secure Query Processing for Private Data Networks," University of Maryland Cybersecurity Center, August 2018.

Teaching Experience

CS 396: Introduction to Cryptography, TA, Winter 2020

MSiA 413: Introduction to Databases and Information Retrieval, TA, Fall 2017, TA

EECS 339: Introduction to Database Systems, TA, Fall 2016, Spring 2017

EECS 395/495-46: Data Science Seminar, TA, Fall 2015

Academic Service

Founder: Northwestern CS Database and Security Reading Group, 2017

Co-Founder: Northwestern CS Ph.D. Advisory Council, 2017

Board Member: Northwestern CS Ph.D. Advisory Council, 2017-2019