Amir Gilad

Amir Gilad

Assistant Professor

The Hebrew University


I am an Assistant Professor (Senior Lecturer) at the Hebrew University of Jerusalem’s School of Computer Science and Engineering.

My research focuses on data analysis, data management, causal analysis, and differential privacy. I am currently working on the development of tools and algorithms that aim to assist users in understanding and gaining insights into data through explanations and causal analysis. I am also studying the privacy implications of providing such explanations.

I am a recipient of the 2017 VLDB Best Paper Award, the 2018 SIGMOD Research Highlight Award, the 2019 Google Ph.D. Fellowship in Structured Data and Database Management, and the SIGMOD 2023 Best Artifact Honorable Mention.

Before joining the Hebrew University, I was a postdoctoral researcher in the Database Group at Duke University, hosted by Prof. Sudeepa Roy, Prof. Ashwin Machanavajjhala, and Prof. Jun Yang. I obtained my Ph.D in Computer Science from Tel Aviv University, where I was advised by Prof. Daniel Deutch. I have also completed both my B.Sc - a double major in Mathematics and Computer Science and my M.Sc in Computer Science at Tel Aviv University.

I am recruiting M.Sc. and Ph.D. students! Please contact me if you are interested in working together.

Recent Publications

(2023). PreFair: Privately Generating Justifiably Fair Synthetic Data. In PVLDB 16(5), 2023.

PDF Link

(2023). DPXPlain: Privately Explaining Aggregate Query Answers. In PVLDB 16(1), 2023.

PDF Link

(2023). Causal What-If and How-To Analysis Using HYPER. In ICDE, 2023.


(2023). FEDEX: An Explainability Framework for Data Exploration Steps. In PVLDB 15(13), 2023.

PDF Link

(2022). Understanding Queries by Conditional Instances. In SIGMOD.

PDF Link


Extended Introduction to Computer Science

Workshop: Google Technologies