| 2026 | EDBT | CoDeC: Constraints-Guided Diverse Counterfactuals. | Avia Asael, Nave Frost, Amir Gilad, Daniel Deutch |
| 2026 | SIGMOD | MonoTune: Analyzing Trend Deviations through Database Repair. | Shunit Agmon, Itai Manor, Brit Youngmann, Benny Kimelfeld, Amir Gilad |
| 2025 | KDD | Refining Labeling Functions with Limited Labeled Data. | Chenjie Li, Amir Gilad, Boris Glavic, Zhengjie Miao, Sudeepa Roy |
| 2025 | SIGMOD | Demonstration of DPClustX: Differentially Private Explanations for Clusters. | Amir Gilad, Tova Milo, Kathy Razmadze, Ron Zadicario |
| 2025 | SIGMOD | CauSumX: Summarized Causal Explanations For Group-By-Average Queries. | Nativ Levy, Michael J. Cafarella, Amir Gilad, Sudeepa Roy, Brit Youngmann |
| 2024 | ICDT | How Database Theory Helps Teach Relational Queries in Database Education (Invited Talk). | Sudeepa Roy, Amir Gilad, Yihao Hu, Hanze Meng, Zhengjie Miao, Kristin Stephens-Martinez, Jun Yang |
| 2024 | SIGMOD | First Workshop on Governance, Understanding and Integration of Data for Effective and Responsible AI (GUIDE-AI). | Abolfazl Asudeh, Sainyam Galhotra, Amir Gilad, Babak Salimi, Brit Youngmann |
| 2023 | ICDE | Causal What-If and How-To Analysis Using HypeR. | Fangzhu Shen, Kayvon Heravi, Oscar Gomez, Sainyam Galhotra, Amir Gilad, Sudeepa Roy, Babak Salimi |
| 2023 | ICDT | The Consistency of Probabilistic Databases with Independent Cells. | Amir Gilad, Aviram Imber, Benny Kimelfeld |
| 2023 | SIGMOD | Characterizing and Verifying Queries Via CINSGEN. | Hanze Meng, Zhengjie Miao, Amir Gilad, Sudeepa Roy, Jun Yang |
| 2022 | SIGMOD | HypeR: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach. | Sainyam Galhotra, Amir Gilad, Sudeepa Roy, Babak Salimi |
| 2022 | SIGMOD | Understanding Queries by Conditional Instances. | Amir Gilad, Zhengjie Miao, Sudeepa Roy, Jun Yang |
| 2021 | CIKM | Explanations for Data Repair Through Shapley Values. | Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer |
| 2021 | ICDE | PITA: Privacy Through Provenance Abstraction. | Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch |
| 2021 | SIGMOD | On Optimizing the Trade-off between Privacy and Utility in Data Provenance. | Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch |
| 2021 | SIGMOD | Synthesizing Linked Data Under Cardinality and Integrity Constraints. | Amir Gilad, Shweta Patwa, Ashwin Machanavajjhala |
| 2020 | CIKM | Towards Inferring Queries from Simple and Partial Provenance Examples. | Amir Gilad, Yuval Moskovitch |
| 2020 | EDBT | Explaining Missing Query Results in Natural Language. | Daniel Deutch, Nave Frost, Amir Gilad, Tomer Haimovich |
| 2020 | SIGMOD | T-REx: Table Repair Explanations. | Daniel Deutch, Nave Frost, Amir Gilad, Oren Sheffer |
| 2020 | SIGMOD | On Multiple Semantics for Declarative Database Repairs. | Amir Gilad, Daniel Deutch, Sudeepa Roy |
| 2019 | EDBT | Reverse-Engineering Conjunctive Queries from Provenance Examples. | Daniel Deutch, Amir Gilad |
| 2018 | ICDE | Interactive Inference of SPARQL Queries Using Provenance. | Efrat Abramovitz, Daniel Deutch, Amir Gilad |
| 2016 | ICDE | QPlain: Query by explanation. | Daniel Deutch, Amir Gilad |
| 2015 | ICDE | selP: Selective tracking and presentation of data provenance. | Daniel Deutch, Amir Gilad, Yuval Moskovitch |
| 2015 | ICDE | Towards web-scale how-provenance. | Daniel Deutch, Amir Gilad, Yuval Moskovitch |