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Iden Kalemaj
I'm a Research Scientist in Meta's Central Applied Science team since 2024.
I work on privacy-preserving machine learning and contribute to the Opacus and PrivacyGuard repos.
I obtained my PhD in Computer Science at Boston University in 2024, advised by Sofya Raskhodnikova.
Prior to that, I studied Mathematics at Princeton University.
I am based in Brooklyn, NYC. After work, I can be found at yoga or dance classes. Feel free to reach out and connect!
Email /
Scholar /
LinkedIn /
Github
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Observational Auditing of Label Privacy
Iden Kalemaj,
Luca Melis,
Maxime Boucher,
Ilya Mironov,
Saeed Malhoujifar
In submission
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Node-Differentially Private Estimation of the Number of Connected Components
Iden Kalemaj,
Sofya Raskhodnikova,
Adam D. Smith,
Charalampos E. Tsourakakis
Principles of Database Systems (PODS), 2023
ACM Transactions on Algorithms, 2025
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Counting Distinct Elements in the Turnstile Model with Differential Privacy under Continual Observation
Palak Jain,
Iden Kalemaj,
Sofya Raskhodnikova,
Satchit Sivakumar,
Adam Smith
Neural Information Processing Systems (NeurIPS), 2023
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Differentially Private Conditional Independence Testing
Iden Kalemaj,
Shiva Prasad Kasiviswanathan,
Aaditya Ramdas
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
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Isoperimetric Inequalities for Real-Valued Functions with Applications to Monotonicity Testing
Hadley Black,
Iden Kalemaj,
Sofya Raskhodnikova
International Colloquium on Automata, Languages and Programming (ICALP), 2023
Random Structures and Algorithms, 2024
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Performative Prediction in a Stateful World
Gavin Brown,
Shlomi Hod,
Iden Kalemaj
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
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Sublinear-Time Computation in the Presence of Online Erasures
Iden Kalemaj,
Sofya Raskhodnikova,
Nithin Varma
Innovations in Theoretical Computer Science (ITCS), 2022
Theory of Computing, 2024
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