Good Allocations from Bad Estimates
with Moritz Hardt
ICLR 2026
[arXiv]
Research conducted while interning at the Max Planck Institute for Intelligent Systems
Selective Omniprediction & Fair Abstention
with Varun Kanade
NeurIPS 2025 (spotlight presentation)
Preliminary version at the Predictions and Uncertainty workshop at COLT 2025
[PDF] [short talk & poster]
How Global Calibration Strengthens Multiaccuracy
with Parikshit Gopalan, Varun Kanade, and Omer Reingold
FOCS 2025
[arXiv] [talk at FOCS]
Reconciling Predictive Multiplicity in Practice
with Tina Behzad, Emily Ruth Diana, and Alexander Williams Tolbert
FAccT 2025
Preliminary version in the Humans, Algorithmic Decision-Making and Society workshop at ICML 2024
[arXiv] [talk at FAccT]
From Independence of Clones to Composition Consistency: A Hierarchy of Barriers to Strategic Nomination
with Ratip Emin Berker, Isaac Robinson, Christopher Ong, Vincent Conitzer, and Edith Elkind
EC 2025
Preliminary version at the Markets, Incentives, and Generative AI workshop at AAAI 2025
[arXiv]
Complexity-Theoretic Implications of Multicalibration
with Cynthia Dwork and Salil Vadhan
STOC 2024 & FORC 2024 (non-archival)
[arXiv] [talk at the Simons Institute] [talk at STOC] [coverage by Quanta Magazine]
Widespread Underestimation of Sensitivity in Differentially Private Libraries and How to Fix It
with Michael Shoemate, Salil Vadhan, and Connor Wagaman
CCS 2022
Preliminary version at the Theory and Practice of Differential Privacy (TPDP) workshop at ICML 2022. Selected for one of the six spotlight talks at TPDP.
[arXiv] [Connor’s talk at TPDP]
Research conducted while interning at OpenDP
SoK: Oblivious Pseudorandom Functions
with Julia Hesse and Anja Lehmann
IEEE EuroS&P 2022. EuroS&P 2022 Distinguished Paper Award Finalist.
[ePrint]
Research conducted while interning at IBM Research
Faster Matrix Inversion and Rank Computation in Finite Fields
with Rasmus Kyng
ITCS 2022
[arXiv] [talk at ITCS]
Research conducted while interning at ETH Zurich
Evaluating Word Embeddings with Categorical Modularity
with Karina Halevy and Damián Blasi
Findings of ACL 2021
[arXiv]
Research conducted at the Harvard Radcliffe Institute for Advanced Study
On the Divisibility of Binomial Coefficients
Ars Math. Contemp. 19 (2020), 297-309
[arXiv]
Research conducted at the Research Science Institute program at MIT
.
Theses
On Learning, Fairness, and Complexity
Master’s thesis at Oxford supervised by professor Varun Kanade, August 2025.
Paper versions: How Global Calibration Strengthens Multiaccuracy (FOCS’25) & Selective Omniprediction & Fair Abstention (NeurIPS’25).
[PDF]
Finding Simple Models of Complex Objects: From Regularity Lemmas to Algorithmic Fairness
Bachelor’s thesis at Harvard supervised by professors Salil Vadhan & Cynthia Dwork, April 2023.
Awarded the Thomas T. Hoopes Prize and the Captain Jonathan Fay Prize.
Paper version: Complexity-Theoretic Implications of Multicalibration (STOC’24).
[PDF]
.
Other workshop papers & manuscripts (from undergrad)
Obvious Independence of Clones
with Ratip Emin Berker, Christopher Ong, and Isaac Robinson
4th International Workshop on Democracy and AI (DemocracAI 2024) at IJCAI 2024. Best student paper award.
[arXiv]
Final project for CS 238 at Harvard (with Prof. Ariel Procaccia)
How To Filter Out Malicious Encrypted Gradients in Federated Learning
with Jordan Barkin, Ratip Emin Berker, and Janet Li
5th AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-24) at AAAI 2024
Final project for CS 242 at Harvard (with Prof. H. T. Kung)
Augmenting Fairness with Welfare: A Framework for Algorithmic Justice
with Isaac Robinson and Connor Wagaman
European Workshop on Algorithmic Fairness (EWAF’23), 2023
[PDF]
Final project for CS 226r at Harvard (with Prof. Cynthia Dwork)
Quantum and Classical Algorithms for Bounded Distance Decoding
with Richard Allen, Ratip Emin Berker, and Michael Gul, 2022
[IACR ePrint]
Final project for CS 227 at Harvard (with Prof. Boaz Barak)
PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability
with Esra Suel and Seth Flaxman
In the Responsible AI and DeepSpatial workshops at KDD 2021
[arXiv]
Project carried out during UROP at Imperial College London
Sílvia Casacuberta Puig 