Shubhankar Mohapatra

• 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, 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. M. Ponomarenko, S. Abedini, M. Shafieinejad, D. B. Emerson, S. Mohapatra, X. He: CAPID: Context-Aware PII Detection for Question-Answering Systems. Proc. EACL 2025 (Volume 4: Student Research).

5. S. Mokhtari, S. Mohapatra, S. Kodeiri, F. Tramèr, G. Kamath: Rethinking Benchmarks for Private Image Classification. IEEE TCDE Bulletin, Dec 2025.

6. S. Mohapatra, S. Sasy, X. He, G. Kamath, O. Thakkar: The Role of Adaptive Optimisers for Honest Private Hyperparameter Selection. AAAI 2022

7. C. Ge, S. Mohapatra, X. He, I. F. Ilyas: Kamino: Constraint-Aware Differentially Private Data Synthesis. Proc. VLDB Endowment, 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 for TVLDB 2025, 2024, 2023, 2020, SIGMOD 2024, 2022, CCS 2022, 2020, AAAI 2022, ICDE 2021, ICML 2021, NeurIPS 2020, EDBT 2019