Aaradhya Pandey

I am a fifth year Graduate student in the Department of Operations Research and Financial Engineering at Princeton University. I am fortunate to work with Sanjeev Kulkarni and Arian Maleki. My research interests are at the interface of probability theory, statistics, and information theory with applications in (quantum) differential privacy, machine unlearning and spin glasses.

I’m applying to postdoctoral positions this Fall (2025) for a Fall 2026 start. If my research interests you, feel free to get in touch.

1. Gaussian certified unlearning in high dimensions: a hypothesis testing approach
   Aaradhya Pandey, Arnab Auddy, Haolin Zou, Arian Maleki, Sanjeev Kulkarni
   arXiv:2510.13094, 2025 (submitted)
   Slides arXiv
2. Exact recovery in Gaussian weighted stochastic block model and planted dense subgraphs: statistical and algorithmic thresholds
   Aaradhya Pandey, Sanjeev Kulkarni
   arXiv:2402.12515, 2024 (submitted)
   Slides arXiv
3. Community detection in the hypergraph stochastic block model and reconstruction on hypertrees
   Yuzhou Gu, Aaradhya Pandey
   Proceedings of the 37th Conference on Learning Theory (COLT 2024), PMLR 247:2166–2203, 30 Jun–03 Jul 2024.
   PMLR arXiv

1. Quantum f-differential privacy: a hypothesis testing approach
   Aaradhya Pandey, Arian Maleki, Sanjeev Kulkarni
   (In preparation)
   Slides arXiv
2. Quantum infinitely divisible states: a genuinely quantum phenomenon
   Aaradhya Pandey, Arian Maleki, Sanjeev Kulkarni
   (In preparation)
   Slides arXiv
3. Distributional machine unlearning: a hypothesis testing approach
   Aaradhya Pandey, Arian Maleki, Sanjeev Kulkarni
   (In preparation)
   Slides arXiv
4. Multivariate version of the Ghirlanda Guerra identities: an application to the matrix of spin correlations for mean-field spin glasses
   Aaradhya Pandey, Arian Maleki, Sanjeev Kulkarni
   (In preparation)
   Slides arXiv
5. Optimal transport as limits of high dimensional statistics: JKO Scheme and a mathematical description of Lasso solution path
   Aaradhya Pandey, Arian Maleki, Sanjeev Kulkarni
   (In preparation)
   Slides arXiv

• [May 2025] Gave a tutorial on Information theory and Differential privacy at TIFR CAM Bangalore, India.
• [May 2025] Presented my work on the Gaussian certified unlearning paper at IISc Bangalore, India.
• [Jan 2025] Presented my work on the Correlation matrix of spin glasses at IISc and TIFR CAM Bangalore, India.
• [Oct 2024] Presented my work on Stochastic block model at Michigan State University, USA.
• [Feb 2024] Our joint work on Stochastic block model was presented by Yuzhou Gu, at the Institute of Advanced Study, USA.

• ORF 445: High Frequency Markets (Spring 2023)
• ORF 387: Networks (Fall 2022)
• MAT 378: Theory of Games (Spring 2023)
• ORF 309: Probability and Stochastic Systems (Fall 2025)
• ORF 245: Fundamentals of Statistics (Fall 2024, 2023)
• ORF 245: Undergraduate statistics (Fall 2024)
• ECE 201: Information and Signals (Spring 2025, 2024)

• Reviewed for journals Information and Inference (IMAIAI), Foundations of Computational Mathematics (FOCM).
• Organized a student reading group in High-dimensional Probability and Statistics, at Princeton.

• ORF 550: Topics in Probability: Probability in High Dimensions (Fall 2021, Grade A)
• ORF 570: Topics in Statistics and Operations Research: Statistical Machine Learning (Fall 2023, Grade A)
• ECO 519: Advanced Econometrics: Nonlinear Models (Fall 2023, Grade A)
• PHY 535: Phase Transitions and Renormalization Group (Fall 2023, Audited)
• MAT 522: Introduction to Partial Differential Equations (Fall 2022, Audited)
• MAT 572: Topics in Combinatorial Optimization (Fall 2022, Audited)
• MAT 577: Topics in Combinatorics: The Probabilistic Method (Spring 2022, Grade A)
• MAT 577: Topics in Combinatorics: Extremal Combinatorics (Spring 2023, Audited)
• MAT 586: Computational methods in Cryo-Electron Microscopy (Spring 2024, Audited)
• MAT 589: Topics in Probability, Statistics and Dynamics: Modern Discrete Probability (Fall 2021, Audited)
• MAT 595: Topics in Mathematical Physics: Mathematical Aspects of Condensed Matter Physics (Spring 2024, Audited)
• MAT 597: Introduction to Mathematical Physics (Spring 2023, Audited)

Email: aaradhyapandey@princeton.edu, aaradhyapandeycs@gmail.com

Office: Room 216, Sherrerd Hall, 98 Charlton Street

Mail: ORFE Department, Princeton University, New Jersey, 08540, USA