Talks

• How Global Calibration Strengthens Multiaccuracy, Carnegie Mellon University EconCS Seminar, Pittsburgh (US), November 2025.
• How Global Calibration Strengthens Multiaccuracy, Stanford Theory Lunch, Stanford (US), October 2025.
• Reconciling predictive multiplicity in practice, FAccT, Athens (Greece), June 2025.
• Understanding the pitfalls of algorithmic predictions, Rhodes Symposium, Oxford (UK), June 2025.
• Algorithmic fairness beyond predictions, Oxbridge Women in Computer Science Conference, Cambridge (UK), May 2025. Best oral presentation award.
• Reconciling predictive multiplicity in practice, Max Planck Institute for Software Systems (virtual), April 2025. Joint with Tina Behzad. Invited.

• (In catalan) Biaixos algorítmics i privadesa de dades: Com podem utilitzar la informàtica teòrica per abordar un problema interdisciplinari?, Quart Cicle de Seminaris de l’Observatori d’Ètica en Intel·ligència Artificial de Catalunya (OEIAC) a la Universitat de Girona (virtual), September 2024. Video. Invited.
• Algorithmic fairness through the lenses of theoretical computer science, 11th World Congress in Probability and Statistics, session on Data Privacy and Algorithmic Fairness in Data Science, Bochum (Germany), August 2024. Invited.
• Complexity-theoretic implications of multicalibration, STOC 2024, Vancouver (Canada), June 2024. Video.
• Bridging the theory and practice of differential privacy & Developing a new theory for algorithmic fairness, Google Algorithms Seminar, Mountain View (US), June 2024. Invited.
• Complexity-theoretic implications of multicalibration, FORC 2024, Boston (US), June 2024.
• New connections between algorithmic fairness, complexity theory, and learning theory, Algorithms and Complexity Theory seminar at Oxford’s Computer Science department, Oxford (UK), May 2024.
• Connections between algorithmic fairness, complexity, and learning, Oxbridge Women in Computer Science Conference, Oxford (UK), May 2024. Best oral presentation award.
• Complexity-theoretic implications of multicalibration, guest lecture at Harvard’s graduate class CS 226r: The Theory of Algorithmic Fairness, March 2024. Invited.
• The Turing Test in modern times: Cryptography, privacy, and fairness, seminar talk for scholars at Rhodes House, Oxford (UK), February 2024.

• Augmenting fairness with welfare: A framework for algorithmic justice, Harvard Bridging Privacy Working Group, August 2023. Joint with Isaac Robinson and Connor Wagaman.
• Augmenting fairness with welfare: A framework for algorithmic justice, European Workshop on Algorithmic Fairness (EWAF’23), Winterthur (Switzerland), June 2023. Joint with Isaac Robinson.
• Complexity-theoretic implications of multicalibration: Hardcore sets, dense models, and pseudoentropy, Simons Institute Workshop on Multigroup Fairness and the Validity of Statistical Judgment, Berkeley (US), April 2023. Video.
• Finding simple models of complex objects: From regularity lemmas to algorithmic fairness, Harvard Math Table, April 2023. Robert Fletcher Rogers Prize.
• Widespread underestimation of sensitivities in DP libraries, Northeastern Network and Distributed Systems Security seminar, Boston (US), April 2023. Joint with Connor Wagaman. Invited.

• Widespread underestimation of sensitivities in DP libraries, CCS’22, Los Angeles (US), November 2022. Joint with Connor Wagaman.
• Oblivious pseudorandom functions, EuroS&P 2022, Genoa (Italy), June 2022.
• Widespread underestimation of sensitivities in DP libraries: vulnerabilities and solutions, Privacy Tools DP seminar in Boston (US), May 2022. Joint with Connor Wagaman.
• Faster sparse matrix inversion rank computation in finite fields, ITCS’22 (virtual), February 2022. Video.
• Faster sparse matrix inversion and rank computation in finite fields, Exact Computing Research Seminar at Université de Montpellier (France), January 2022. Invited.

• Faster sparse matrix inversion and rank computation in finite fields, Google Zurich Algorithms & Optimization Group Seminar (virtual), December 2021.
• Verification of differentially private algorithms, Harvard PRISE final presentation (virtual), August 2021.
• PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability, Responsible AI workshop and DeepSpatial workshop at KDD 2021 (virtual), August 2021.
• Oblivious pseudorandom functions (OPRFs): origins and modern applications, IBM Research Security Seminar, Zurich (Switzerland), May 2021.

• Why are p-adic numbers useful for fast linear algebra algorithms?, Harvard Math Table (poster), December 2020.
• On the divisibility of binomial coefficients, final presentation at the Research Science Institute at MIT, Boston (US), August 2017. Video. Research Science Institute final presentation student award.