Shubhankar Mohapatra
Research Area
- Data Privacy
- Generative AI
- Databases
- Differential Privacy
- President's Graduate Scholarship
- Ontario Graduate Scholarship
- Cheriton Scholarship
- Queen Elizabeth Scholarship in Science & Technology (QEII-GSST)
- MITACS Accelerate Fellowship
- NRF PD Grant
- Vector Institute Research Grant
1. S. Mohapatra, A.Gilad, B.Kimelfeld & X.He. Inconsistency Measures for Differentially Private Databases. Proc. ACM SIGMOD Int. Conf. on Management of Data. 3(3): 140:1-140:27,2025.
2. S.Zhang, H.Sun, K.Knopf, S.Mohapatra, W.Pang, C. Wang, Y.Wang, M.Shafieinejad, D. Emerson & X.He. FedDPSyn: Federated Tabular Data Synthesis with Computational Differential Privacy. TPDP 2025.
3. S.Abedini, S.Mohapatra, D.B.Emerson, M.Shafieinejad, J.C.Cresswell, X.He. MaskSQL: Safeguarding Privacy for LLM-Based Text-to-SQL via Abstraction. NeurIPS 2025 (Regulatable ML Workshop)
4. Mariia Ponomarenko, Sepideh Abedini, Masoumeh Shafieinejad, DB Emerson, Shubhankar Mohapatra, Xi He. CAPID: Context-Aware PII Detection for Question-Answering Systems. Proc. EACL 19 (Volume 4: Student Research).
5. S.Mokhtari, S. Mohapatra, S.Kodeiri , F.Tramèr, & G.Kamath. Rethinking Benchmarks for Private Image Classification. IEEE TCDE Bulletin, December 2025.
6. S. Mohapatra, S. Sasy, X. He, G. Kamath & O.Thakkar. The Role of Adaptive Optimisers for Honest Private Hyperparameter Selection. AAAI 2022: 7806-7813.
7. C. Ge, S. Mohapatra, X. He & I.F.Ilyas. Kamino: Constraint-Aware Differentially Private Data Synthesis. Proc. VLDB Endow. 14(10): 1886-1899, 2021.
- Program Committee: AAAI 2026, SeQureDB 2026, TPDP 2026, 2025, 2024, OnDBD 2024
- Program Co-chair: GradConf2025
- Course Material Curator: AI for Differential Privacy at the University of Waterloo
- External Reviewer: TVLDB 2025, 2024, 2023, 2020, SIGMOD 2024, 2022, CCS 2022, 2020, AAAI 2022, ICDE 2021, ICML 2021, NeurIPS 2020, EDBT 2019